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Objectives: The study aim was to conduct a systematic review of the literature reporting the application of radiomics to imaging techniques in patients with ovarian lesions., Methods: MEDLINE/PubMed, Web of Science, Scopus, EMBASE, Ovid and ClinicalTrials.gov were searched for relevant articles. Using PRISMA criteria, data were extracted from short-listed studies. Validity and bias were assessed independently by 2 researchers in consensus using the Quality in Prognosis Studies (QUIPS) tool. Radiomic Quality Score (RQS) was utilised to assess radiomic methodology., Results: After duplicate removal, 63 articles were identified, of which 33 were eligible. Fifteen assessed lesion classifications, 10 treatment outcomes, 5 outcome predictions, 2 metastatic disease predictions and 1 classification/outcome prediction. The sample size ranged from 28 to 501 patients. Twelve studies investigated CT, 11 MRI, 4 ultrasound and 1 FDG PET-CT. Twenty-three studies (70%) incorporated 3D segmentation. Various modelling methods were used, most commonly LASSO (least absolute shrinkage and selection operator) (10/33). Five studies (15%) compared radiomic models to radiologist interpretation, all demonstrating superior performance. Only 6 studies (18%) included external validation. Five studies (15%) had a low overall risk of bias, 9 (27%) moderate, and 19 (58%) high risk of bias. The highest RQS achieved was 61.1%, and the lowest was - 16.7%., Conclusion: Radiomics has the potential as a clinical diagnostic tool in patients with ovarian masses and may allow better lesion stratification, guiding more personalised patient care in the future. Standardisation of the feature extraction methodology, larger and more diverse patient cohorts and real-world evaluation is required before clinical translation., Clinical Relevance Statement: Radiomics shows promising results in improving lesion stratification, treatment selection and outcome prediction. Modelling with larger cohorts and real-world evaluation is required before clinical translation., Key Points: • Radiomics is emerging as a tool for enhancing clinical decisions in patients with ovarian masses. • Radiomics shows promising results in improving lesion stratification, treatment selection and outcome prediction. • Modelling with larger cohorts and real-world evaluation is required before clinical translation., (© 2023. European Society of Radiology (ESR).)

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. Risk of bias was assessed using PROBAST. Information about each model was tabulated and summary statistics were reported. The study was registered on PROSPERO (CRD42022334730) and PRISMA 2020 reporting guidelines were followed. Searches identified 1573 records, of which 45 were eligible for inclusion. These studies contained 80 models of interest, including 37 diagnostic models, 22 prognostic models, and 21 other diagnostically relevant models. Common tasks included treatment response prediction (11/80), malignancy status classification (10/80), stain quantification (9/80), and histological subtyping (7/80). Models were developed using 1-1375 histopathology slides from 1-776 ovarian cancer patients. A high or unclear risk of bias was found in all studies, most frequently due to limited analysis and incomplete reporting regarding participant recruitment. Limited research has been conducted on the application of AI to histopathology images for diagnostic or prognostic purposes in ovarian cancer, and none of the models have been demonstrated to be ready for real-world implementation. Key aspects to accelerate clinical translation include transparent and comprehensive reporting of data provenance and modelling approaches, and improved quantitative evaluation using cross-validation and external validations. This work was funded by the Engineering and Physical Sciences Research Council., (© 2023. Nature Publishing Group UK.)

Background: The open-label, single-arm, multicenter ORZORA trial (NCT02476968) evaluated the efficacy and safety of maintenance olaparib in patients with platinum-sensitive relapsed ovarian cancer (PSR OC) who had tumor BRCA mutations (BRCAm) of germline (g) or somatic (s) origin or non-BRCA homologous recombination repair mutations (HRRm) and were in response to their most recent platinum-based chemotherapy after ≥2 lines of treatment., Methods: Patients received maintenance olaparib capsules (400 mg twice daily) until disease progression. Prospective central testing at screening determined tumor BRCAm status and subsequent testing determined gBRCAm or sBRCAm status. Patients with predefined non-BRCA HRRm were assigned to an exploratory cohort. The co-primary endpoints were investigator-assessed progression-free survival (PFS; modified Response Evaluation Criteria in Solid Tumors v1.1) in BRCAm and sBRCAm cohorts. Secondary endpoints included health-related quality of life (HRQoL) and tolerability., Results: 177 patients received olaparib. At the primary data cut-off (17 April 2020), the median follow-up for PFS in the BRCAm cohort was 22.3 months. The median PFS (95% CI) in BRCAm, sBRCAm, gBRCAm and non-BRCA HRRm cohorts was 18.0 (14.3-22.1), 16.6 (12.4-22.2), 19.3 (14.3-27.6) and 16.4 (10.9-19.3) months, respectively. Most patients with BRCAm reported improvements (21.8%) or no change (68.7%) in HRQoL and the safety profile was as expected., Conclusions: Maintenance olaparib had similar clinical activity in PSR OC patients with sBRCAm and those with any BRCAm. Activity was also observed in patients with a non-BRCA HRRm. ORZORA further supports use of maintenance olaparib in all patients with BRCA-mutated, including sBRCA-mutated, PSR OC., Competing Interests: Declaration of Competing Interest Sandro Pignata: Honoraria from AstraZeneca, Merck Sharp & Dohme (MSD), Roche, Pfizer, GlaxoSmithKline (GSK) and Clovis Pharma; and research funding from Roche, MSD, AstraZeneca and Pfizer. Amit Oza: Principal investigator of investigator-initiated studies with AstraZeneca; institutional grant funding from AstraZeneca; and steering committee member (non-compensated) for AstraZeneca, Clovis Oncology and GSK. Geoff Hall: Research funding from IQVIA. Beatriz Pardo: Research funding from AstraZeneca, GSK, Clovis and MSD. Radoslaw Madry: Advisory board participation for AstraZeneca, Roche and GSK; and personal fees from AstraZeneca, Roche and GSK. David Cibula: Advisory board participation for AstraZeneca, Roche, Genmab, SOTIO, Merck and GSK. Jaroslav Klat: Reports no disclosures. Ana Montes: Reports no disclosures. Rosalind Glasspool: Principal investigator for trials sponsored by AstraZeneca, Clovis, Tesaro, Immunogen, Pfizer and Lilly; research funding from Clovis, Boehringer Ingelheim and Lilly/Ignyta; institution research funding from Tesaro; institutional fees from Novartis and personal fees from AstraZeneca, MSD, Clovis, Tesaro, GSK, Immunogen and SOTIO. Nicoletta Colombo: Personal fees from AstraZeneca, MSD, Roche, Tesaro, GSK, Clovis Oncology, PharmaMar, Pfizer, Amgen, Novartis, BIODCAD and Immunogen. Imre Pete: Reports no disclosures. Ana Herrero Ibáñez: Consulting/advisory board participation for GSK; speakers’ bureau participation for Clovis, GSK, MSD and PharmaMar; and research funding from AstraZeneca and Roche. Margarita Romeo Marín: Institution research funding from AstraZeneca, GSK, Clovis and Pfizer. Personal fees from MSD and GSK. Rumya Ilieva: Reports no disclosures. Constanta Timcheva: Principal investigator of clinical trials of AstraZeneca, Roche, Novartis, Pfizer and Merck; and member of advisory boards of Astellas, Servier and Novartis. Massimo Di Maio: Principal investigator of clinical trials of Roche, Merck, BeiGene, Novartis, Pfizer and Exelixis; member of advisory boards of AstraZeneca, Roche, Novartis, Pfizer, Eisai, Astellas, Janssen, Merck and Amgen; institutional research funding from Tesaro – GlaxoSmithKline. Christopher Blakeley: AstraZeneca employment and stock ownership. Rosie Taylor: AstraZeneca contractor. Alan Barnicle: AstraZeneca employment and stock ownership. Andrew Clamp: Research funding from AstraZeneca; and honoraria from AstraZeneca, Clovis Oncology, GSK/Tesaro and Eisai., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: Much drug development and published analysis for epithelial ovarian cancer (EOC) focuses on early-line treatment. Full sequences of treatment from diagnosis to death and the impact of later lines of therapy are rarely studied. We describe the establishment of an international network of cancer centers configured to compare real-world treatment pathways in UK, Portugal, Germany, South Korea, France and Romania (the Ovarian Real-World International Consortium; ORWIC)., Methods: 3344 patients diagnosed with EOC (2012-2018) were analysed using a common data model and hub and spoke programming approach applied to existing electronic medical records. Consistent definition of line of therapy between sites and an efficient approach to analysis within the limitations of local information governance was achieved., Results: Median age of participants was 53-67 years old and 5-29% were ECOG >1. Between 62% and 84% of patients were diagnosed with late-stage disease (FIGO III-IV). Sites treating younger and fitter patients had higher rates of debulking surgery for those diagnosed at late stage than sites with older, more frail patients. At least 21% of patients treated with systemic anti-cancer therapy (SACT) had recurrent disease following second-line therapy (2L); up to 11 lines of SACT treatment were recorded for some patients. Platinum-based SACT was consistently used across sites at 1L, but choices at 2L varied, with hormone therapies commonly used in the UK and Portugal. The use (and type) of maintenance therapy following 1L also varied. Beyond 2L, there was little consensus between sites on treatment choice: trial compounds and unspecified combinations of other agents were common., Discussion: Specific treatment sequences are reported up to 4L and the establishment of this network facilitates future analysis of comparative outcomes per line of treatment with the aim of optimizing available options for patients with recurrent EOC. In particular, this real-world network can be used to assess the growing use of PARP inhibitors. The real-world optimization of advanced line treatment will be especially important for patients not usually eligible for involvement with clinical trials. The resources to enable this analysis to be implemented elsewhere are supplied and the network will seek to grow in coverage of further sites., Competing Interests: Authors BL, WS, HF, NN and MG-K were employed by IQVIA Oncology Evidence Network. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Cheeseman, Levick, Sopwith, Fenton, Nam, Kim, Lim, Martin, Frenel, Bocquet, Kubelac, Achimas-Cadariu, Vlad, Chevrier, Rouzier, Carton, Savva-Bordalo, Magalhães, Borges, Wolf, Becker, Niklas, Guergova-Kuras and Hall.)

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. In this study impactful models are trained on a widely used open-source data and tested on an external test set and a hospital dataset, for the task of classifying chest X-rays into one of three classes: COVID-19, non-COVID pneumonia and no-pneumonia. Classification performance of the models investigated is evaluated through ROC curves, confusion matrices and standard classification metrics. Explainability modules are implemented to explore the image features most important to classification. Data analysis and model evalutions show that the popular open-source dataset COVIDx is not representative of the real clinical problem and that results from testing on this are inflated. Dependence on open-source data can leave models vulnerable to bias and confounding variables, requiring careful analysis to develop clinically useful/viable AI tools for COVID-19 detection in chest X-rays.

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 application uses data items hospitals in England are mandated to collect as part of the Cancer Outcomes and Services Dataset (COSD), to provide clinical insight into survival outcomes, population distributions, service demands, waiting times, geographical case distributions and treatment information in real-time or near real-time. Development was guided by end user needs through the use of panels of clinical and non-clinical end users.

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. In this current protocol, we propose the linkage of Patient Reported Outcomes Measures data to the above data for a subset of this population. The aim of this study is to investigate the full impact of living with and beyond a cancer diagnosis compared to age and gender matched controls. A secondary aim is to test the feasibility of the collection of Patient Reported Outcomes Measures (PROMS) data and the linkage procedures of the PROMs data to electronic health records data., Materials and Methods: This is a cross-sectional study, aiming to recruit participants treated at the Leeds Teaching Hospitals National Health Service Trust. Eligible patients will be cancer survivors at around 5 years post-diagnosis (breast, colorectal and ovarian cancer) and non-cancer patient matched controls attending dermatology out-patient clinics. They will be identified by running a query on the Leeds Teaching Hospitals Trust patient records system. Approximately 6000 patients (2000 cases and 4000 controls) will be invited to participate via post. Participants will be invited to complete PROMs assessing factors such as quality of life and finances, which can be completed on paper or online (surveys includes established instruments, and bespoke instruments (demographics, financial costs). This PROMs data will then be linked to routinely collected de-identified data from patient's electronic primary care and hospital records., Discussion: This innovative work aims to create a truly 'comprehensive patient record' to provide a broad picture of what happens to cancer patients across their cancer pathway, and the long-term impact of cancer treatment. Comparisons can be made between the cases and controls, to identify the aspects of life that has had the greatest impact following a cancer diagnosis. The feasibility of linking PROMs data to electronic health records can also be assessed. This work can inform future support offered to people living with and beyond a cancer diagnosis, clinical practice, and future research methodologies., Competing Interests: The authors have declared that no competing interests exist.

Objectives: To develop and validate tests to assess the risk of any cancer for patients referred to the NHS Urgent Suspected Cancer (2-week wait, 2WW) clinical pathways., Setting: Primary and secondary care, one participating regional centre., Participants: Retrospective analysis of data from 371 799 consecutive 2WW referrals in the Leeds region from 2011 to 2019. The development cohort was composed of 224 669 consecutive patients with an urgent suspected cancer referral in Leeds between January 2011 and December 2016. The diagnostic algorithms developed were then externally validated on a similar consecutive sample of 147 130 patients (between January 2017 and December 2019). All such patients over the age of 18 with a minimum set of blood counts and biochemistry measurements available were included in the cohort., Primary and Secondary Outcome Measures: sensitivity, specificity, negative predictive value, positive predictive value, Receiver Operating Characteristic (ROC) curve Area Under Curve (AUC), calibration curves RESULTS: We present results for two clinical use-cases. In use-case 1, the algorithms identify 20% of patients who do not have cancer and may not need an urgent 2WW referral. In use-case 2, they identify 90% of cancer cases with a high probability of cancer that could be prioritised for review., Conclusions: Combining a panel of widely available blood markers produces effective blood tests for cancer for NHS 2WW patients. The tests are affordable, and can be deployed rapidly to any NHS pathology laboratory with no additional hardware requirements., Competing Interests: Competing interests: RS, KLL, MDN, JRS, NS and GT are employed by and are shareholders in PinPoint Data Science. MM has been employed as a consultant to PinPoint Data Science in October to November 2020. Both the University of Leeds and Leeds Teaching Hospitals Trust have a royalty agreement with PinPoint Data Science, meaning that those institutions are likely to benefit financially in the event of PinPoint being commercially successful., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Background: The use of linked healthcare data in research has the potential to make major contributions to knowledge generation and service improvement. However, using healthcare data for secondary purposes raises legal and ethical concerns relating to confidentiality, privacy and data protection rights. Using a linkage and anonymisation approach that processes data lawfully and in line with ethical best practice to create an anonymous (non-personal) dataset can address these concerns, yet there is no set approach for defining all of the steps involved in such data flow end-to-end. We aimed to define such an approach with clear steps for dataset creation, and to describe its utilisation in a case study linking healthcare data., Methods: We developed a data flow protocol that generates pseudonymous datasets that can be reversibly linked, or irreversibly linked to form an anonymous research dataset. It was designed and implemented by the Comprehensive Patient Records (CPR) study in Leeds, UK., Results: We defined a clear approach that received ethico-legal approval for use in creating an anonymous research dataset. Our approach used individual-level linkage through a mechanism that is not computer-intensive and was rendered irreversible to both data providers and processors. We successfully applied it in the CPR study to hospital and general practice and community electronic health record data from two providers, along with patient reported outcomes, for 365,193 patients. The resultant anonymous research dataset is available via DATA-CAN, the Health Data Research Hub for Cancer in the UK., Conclusions: Through ethical, legal and academic review, we believe that we contribute a defined approach that represents a framework that exceeds current minimum standards for effective pseudonymisation and anonymisation. This paper describes our methods and provides supporting information to facilitate the use of this approach in research., Competing Interests: The authors have declared that no competing interests exist.

Objectives: To report characteristics, treatment and overall survival (OS) trends, by stage and pathology, of patients diagnosed with non-small cell lung cancer (NSCLC) at Leeds Teaching Hospital NHS Trust in 2007-2018., Design: Retrospective cohort study based on electronic medical records., Setting: Large NHS university hospital in Leeds., Participants: 3739 adult patients diagnosed with incident NSCLC from January 2007 to August 2017, followed up until March 2018., Main Outcome Measures: Patient characteristics at diagnosis, treatment patterns and OS., Results: 34.3% of patients with NSCLC were clinically diagnosed (without pathological confirmation). Among patients with known pathology, 45.2% had non-squamous cell carcinoma (NSQ) and 33.3% had squamous cell carcinoma (SQ). The proportion of patients diagnosed at stage I increased (16.4%-27.7% in 2010-2017); those diagnosed at stage IV decreased (57.0%-39.1%). Surgery was the most common initial treatment for patients with pathologically confirmed stage I NSCLC. Use of radiotherapy alone increased over time in patients with clinically diagnosed stage I NSCLC (39.1%-60.3%); chemoradiation increased in patients with stage IIIA NSQ (21.6%-33.3%) and SQ (24.2%-31.9%). Initial treatment with systemic anticancer therapy (SACT) increased in patients with stages IIIB-IV NSQ (49.0%-67.5%); the proportion of untreated patients decreased (30.6%-15.0%). Median OS improved for patients diagnosed with stage I NSQ and SQ and stage IIIA NSQ over time. Median OS for patients with stages IIIB-IV NSQ and SQ remained stable, <10% patients were alive 3 years after diagnosis. Median OS for clinically diagnosed stages IIIB-IV patients was 1.2 months in both periods., Conclusions: OS for stage I and IIIA patients improved over time, likely due to increased use of stereotactic ablative radiation, surgery (stage I) and chemoradiation (stage IIIA). Conversely, OS outcomes remained poor for stage IIIB-IV patients despite increasing use of SACT for NSQ. Many patients with advanced-stage disease remained untreated., Competing Interests: Competing interests: GH is an employee of the University of Leeds and holds an honorary contract with Leeds Teaching Hospital NHS Trust. He leads the Leeds Teaching Hospitals NHS Trust real-world evidence team collaboration with IQVIA and, as part of this collaboration, IQVIA funds the staff who support this work. He also reports partial grant funding for a collaboration outside this study from IQVIA. MS was an employee at Leeds Teaching Hospital NHS Trust at the time of the study and he holds an honorary contract with Leeds Teaching Hospital NHS Trust. He receives consultancy fees from BMS. MS, MT and MR are employees of IQVIA. WS and SC are subcontracted to IQVIA and hold honorary contracts with Leeds Teaching Hospital NHS Trust. CC, MMD and JRP are employees of BMS. CC and JRP report stock ownership in BMS. LL was contracted (paid) as a consultant by BMS to support the I-O Optimise initiative and is an employee of Epi-Fit., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The main challenge in the pathway analysis of cancer treatments is the complexity of the process. Process mining is one of the approaches that can be used to visualize and analyze these complex pathways. In this study, our purpose was to use process mining to explore variations in the treatment pathways of endometrial cancer. We extracted patient data from a hospital information system, created the process model, and analyzed the variations of the 62-day pathway from a General Practitioner referral to the first treatment in the hospital. We also analyzed the variations based on three different criteria: the type of the first treatment, the age at diagnosis, and the year of diagnosis. This approach should be of interest to others dealing with complex medical and healthcare processes.

Objectives: To assess how a decade of developments in systematic anticancer therapy (SACT) for advanced non-small cell lung cancer (NSCLC) affected overall survival (OS) in a large UK University Hospital., Design: Real-world retrospective observational cohort study using existing data recorded in electronic medical records., Setting: A large National Health Service (NHS) university teaching hospital serving 800 000 people living in a diverse metropolitan area of the UK., Participants: 2119 adults diagnosed with advanced NSCLC (tumour, node, metastasis stage IIIB or IV) between 2007 and 2017 at Leeds Teaching Hospitals NHS Trust., Main Outcomes and Measures: OS following diagnosis and the analysis of factors associated with receiving SACT., Results: Median OS for all participants was 2.9 months, increasing for the SACT-treated subcohort from 8.4 months (2007-2012) to 9.1 months (2013-2017) (p=0.02); 1-year OS increased from 33% to 39% over the same period for the SACT-treated group. Median OS for the untreated subcohort was 1.6 months in both time periods. Overall, 30.6% (648/2119) patients received SACT; treatment rates increased from 28.6% (338/1181) in 2007-2012 to 33.0% (310/938) in 2013-2017 (p=0.03). Age and performance status were independent predictors for SACT treatment; advanced age and higher performance status were associated with lower SACT treatment rates., Conclusion: Although developments in SACT during 2007-2017 correspond to some changes in survival for treated patients with advanced NSCLC, treatment rates remain low and the prognosis for all patients remains poor., Competing Interests: Competing interests: REAL-Oncology is a collaboration between Leeds Teaching Hospital NHS Trust and IQVIA. Commercial clients of IQVIA include Bristol Myers Squibb (BMS), which funded the project this work is based on. REAL-Oncology retains all operational, scientific and communications controls. GH is an employee of the University of Leeds and holds an honorary contract with Leeds Teaching Hospital NHS Trust. GH leads the Leeds Teaching Hospitals NHS Trust real-world evidence team collaboration with IQVIA and, as part of this collaboration, IQVIA fund the staff who support this work. GH also reports partial grant funding for a collaboration outside this study from IQVIA. MS was an employee at Leeds Teaching Hospital NHS Trust at the time of the study and he holds an honorary contract with Leeds Teaching Hospital NHS Trust. MS, MT and MR are employees of IQVIA. WS and SC are subcontracted to IQVIA and hold honorary contracts with Leeds Teaching Hospital NHS Trust. MS receives consultancy fees from BMS. CC, MMD, JRP and JCO’D are employees of BMS. CC and JRP report stock ownership in BMS. LL was contracted (paid) as consultant by BMS to support the I-O Optimise initiative and is an employee of Epi-Fit. There are no further conflicts of interest., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: To estimate the impact of the COVID-19 pandemic on cancer care services and overall (direct and indirect) excess deaths in people with cancer., Methods: We employed near real-time weekly data on cancer care to determine the adverse effect of the pandemic on cancer services. We also used these data, together with national death registrations until June 2020 to model deaths, in excess of background (pre-COVID-19) mortality, in people with cancer. Background mortality risks for 24 cancers with and without COVID-19-relevant comorbidities were obtained from population-based primary care cohort (Clinical Practice Research Datalink) on 3 862 012 adults in England., Results: Declines in urgent referrals (median=-70.4%) and chemotherapy attendances (median=-41.5%) to a nadir (lowest point) in the pandemic were observed. By 31 May, these declines have only partially recovered; urgent referrals (median=-44.5%) and chemotherapy attendances (median=-31.2%). There were short-term excess death registrations for cancer (without COVID-19), with peak relative risk (RR) of 1.17 at week ending on 3 April. The peak RR for all-cause deaths was 2.1 from week ending on 17 April. Based on these findings and recent literature, we modelled 40% and 80% of cancer patients being affected by the pandemic in the long-term. At 40% affected, we estimated 1-year total (direct and indirect) excess deaths in people with cancer as between 7165 and 17 910, using RRs of 1.2 and 1.5, respectively, where 78% of excess deaths occured in patients with ≥1 comorbidity., Conclusions: Dramatic reductions were detected in the demand for, and supply of, cancer services which have not fully recovered with lockdown easing. These may contribute, over a 1-year time horizon, to substantial excess mortality among people with cancer and multimorbidity. It is urgent to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks., Competing Interests: Competing interests: ML has received honoraria from Pfizer, EMD Serono and Roche for presentations unrelated to this research, and an unrestricted educational grant from Pfizer for research unrelated to the research presented in this paper. AB has received research funding from AstraZeneca. MF has received research funding from AstraZeneca, Boehringer Ingelheim, Merck and MSD and honoraria from Achilles, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Meyers Squibb, Celgene, Guardant Health, Merck, MSD, Nanobiotix, Novartis, Pharmamar, Roche and Takeda for advisory roles or presentations unrelated to this research. GF receives funding from companies that manufacture drugs for hepatitis C virus (AbbVie, Gilead, MSD) and is a consultant for GSK, Arbutus and Shionogi in areas unrelated to this research., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

The area of process change over time is a particular concern in healthcare, where patterns of care emerge and evolve in response to individual patient needs. We propose a structured approach to analyse process change over time that is suitable for the complex domain of healthcare. Our approach applies a qualitative process comparison at three levels of abstraction: a holistic perspective (process model), a middle-level perspective (trace), and a fine-grained detail (activity). Our aim was to detect change points, localise and characterise the change, and unravel/understand the process evolution. We illustrate the approach using a case study of cancer pathways in Leeds where we found evidence of change points identified at multiple levels. In this paper, we extend our study by analysing the miners used in process discovery and providing a deeper analysis of the activity of investigation in trace and activity levels. In the experiment, we show that this qualitative approach provides a useful understanding of process change over time. Examining change at three levels provides confirmatory evidence of process change where perspectives agree, while contradictory evidence can lead to focused discussions with domain experts. This approach should be of interest to others dealing with processes that undergo complex change over time.

Purpose: Platinum resistance in ovarian cancer is associated with epigenetic modifications. Hypomethylating agents (HMA) have been studied as carboplatin resensitizing agents in ovarian cancer. This randomized phase II trial compared guadecitabine, a second-generation HMA, and carboplatin (G+C) against second-line chemotherapy in women with measurable or detectable platinum-resistant ovarian cancer., Patients and Methods: Patients received either G+C (guadecitabine 30 mg/m 2 s.c. once-daily for 5 days and carboplatin) or treatment of choice (TC; topotecan, pegylated liposomal doxorubicin, paclitaxel, or gemcitabine) in 28-day cycles until progression or unacceptable toxicity. The primary endpoint was progression-free survival (PFS); secondary endpoints were RECIST v1.1 and CA-125 response rate, 6-month PFS, and overall survival (OS)., Results: Of 100 patients treated, 51 received G+C and 49 received TC, of which 27 crossed over to G+C. The study did not meet its primary endpoint as the median PFS was not statistically different between arms (16.3 weeks vs. 9.1 weeks in the G+C and TC groups, respectively; P = 0.07). However, the 6-month PFS rate was significantly higher in the G+C group (37% vs. 11% in TC group; P = 0.003). The incidence of grade 3 or higher toxicity was similar in G+C and TC groups (51% and 49%, respectively), with neutropenia and leukopenia being more frequent in the G+C group., Conclusions: Although this trial did not show superiority for PFS of G+C versus TC, the 6-month PFS increased in G+C treated patients. Further refinement of this strategy should focus on identification of predictive markers for patient selection., (©2019 American Association for Cancer Research.)

Objectives: 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. Patients and Methods: 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. Summary and descriptive statistics were calculated for categorical and continuous variables as appropriate. The Kaplan-Meier method was used to estimate median survival and Cox regression proportional hazards model was used to explore relationships between clinical variables and outcome. Results: Two hundred and sixteen patients made up the study cohort, with a median age of 66 years (range: 35-83) and 72.7% being male. First-line treatment consisted of either a cisplatin- (44%) or carboplatin-based regimen (48%) in the majority of patients. Twenty seven percent of patients received a second-line of treatment (most commonly single-agent paclitaxel) following a first-line platinum containing regimen. Grade 4 neutropenia was observed in 19 and 27% of those treated with a first-line cisplatin- and carboplatin-based regimen, respectively. The median overall survival (mOS) of the study cohort was estimated to be 16.2 months (IQR: 10.6-28.3 months). Receipt by patients of cisplatin-based chemotherapy was associated with a longer mOS and this association persisted when survival analysis was adjusted for age, sex, performance status and presence of distant metastases. Conclusions: This study provides a useful benchmark for outcomes achieved in a real-world setting for patients with locally advanced or metastatic UC treated with chemotherapy in the immediate pre-immunotherapy era., (Copyright © 2020 Cheeseman, Thompson, Sopwith, Godden, Seshagiri, Adedokun, Zucker, Jain, Kotwal, Prescott, Henry, Joseph, Chilka, Roulson, Weston, Burbidge, Brown, Jagdev, Ralph, Hall and Vasudev.)

Background: Study aimed to characterise treatment and outcomes for patients with hormone receptor positive (HR+), human epidermal growth factor 2 negative (HER2-) metastatic breast cancer (MBC) within a large regional cancer centre, as a benchmark for evaluating real-world impact of novel therapies., Methods: Retrospective longitudinal cohort, using electronic patient records of adult females with a first diagnosis of HR+/HER2- MBC January 2012-March 2018., Results: One hundred ninety-six women were identified with HR+/HER2- MBC. Median age was 67 years, 85.2% were post-menopausal and median time between primary diagnosis and metastasis was 5.4 years. Most (75.1%) patients received endocrine therapy as first line systemic treatment (1st LoT); use of 1st LoT chemotherapy halved between 2012 and 2017. Patients receiving 1st LoT chemotherapy were younger and more likely to have visceral metastasis (p < 0.01). Median OS was 29.5 months and significantly greater for patients with exclusively non-visceral metastasis (p < 0.01). The adjusted hazard ratio for death of patients with visceral (or CNS) metastasis was 1.91 relative to those with exclusively non-visceral metastasis., Conclusions: Diverse endocrine therapies predominate as 1st LoT for patients with HR+/HER2- MBC, chemotherapy being associated with more aggressive disease in younger patients, emphasising the importance of using effective and tolerable therapies early.

There is a growing body of literature on process mining in healthcare. Process mining of electronic health record systems could give benefit into better understanding of the actual processes happened in the patient treatment, from the event log of the hospital information system. Researchers report issues of data access approval, anonymisation constraints, and data quality. One solution to progress methodology development is to use a high-quality, freely available research dataset such as Medical Information Mart for Intensive Care III, a critical care database which contains the records of 46,520 intensive care unit patients over 12 years. Our article aims to (1) explore data quality issues for healthcare process mining using Medical Information Mart for Intensive Care III, (2) provide a structured assessment of Medical Information Mart for Intensive Care III data quality and challenge for process mining, and (3) provide a worked example of cancer treatment as a case study of process mining using Medical Information Mart for Intensive Care III to illustrate an approach and solution to data quality challenges. The electronic health record software was upgraded partway through the period over which data was collected and we use this event to explore the link between electronic health record system design and resulting process models.

Background: The 'Two Week Wait' policy aims to ensure patients with suspected cancer are seen within two weeks of referral. However, patient non-attendance can result in this target being missed. This study aimed to identify predictors of non-attendance; and analyse the relationship between attendance and outcomes including cancer diagnosis and early mortality., Methods: A cohort study of 109,433 adults registered at 105 general practices, referred to a cancer centre within a large NHS hospital trust (April 2009 to December 2016) on the 'Two Week Wait' pathway., Results: 5673 (5.2%) patients did not attend. Non-attendance was largely predicted by patient factors (younger and older age, male gender, greater deprivation, suspected cancer site, earlier year of referral, greater distance to the hospital) over practice factors (greater deprivation, lower Quality and Outcomes Framework score, lower cancer conversion rate, lower cancer detection rate). 10,360 (9.6%) patients were diagnosed with cancer within six months of referral (9.8% attending patients, 5.6% non-attending patients). Among these patients, 2029 (19.6%) died within 12 months of diagnosis: early mortality risk was 31.3% in non-attenders and 19.2% in attending patients., Conclusions: Non-attendance at urgent referral appointments for suspected cancer involves a minority of patients but happens in predictable groups. Cancer diagnosis was less likely in non-attending patients but these patients had worse early mortality outcomes than attending patients. The study findings have implications for cancer services and policy., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: The 2-week-wait urgent referral policy in the UK has sought to improve cancer outcomes by accelerating diagnosis and treatment. However, around 5-7% of symptomatic referred patients cancel or do not attend their hospital appointment. While subsequent cancer diagnosis was less likely in non-attenders, those with a diagnosis had worse early mortality outcomes., Aim: To examine how interpersonal, communication, social, and organisational factors influence a patient's non-attendance., Design and Setting: Qualitative study in GP practices in one Northern English city., Method: In-depth, individual interviews were undertaken face-to-face or by telephone between December 2016 and May 2018, followed by thematic framework analysis., Results: In this study 21 GPs, and 24 patients who did not attend or had cancelled their appointment were interviewed, deriving a range of potential explanations for non-attendance, including: system flaws; GP difficulties with booking appointments; patient difficulties with navigating the appointment system, particularly older patients and those from more deprived areas; patients leading 'difficult lives'; and patients' expectations of the referral, informed by their beliefs, circumstances, priorities, and the perceived prognosis. GPs recognised the importance of communication with the patient, particularly the need to tailor communication to perceived patient understanding and anxiety. GPs and practices varied in their responses to patient non-attendance, influenced by time pressures and perceptions of patient responsibility., Conclusion: Failure to be seen within 2 weeks of urgent referral resulted from a number of patient and provider factors. The urgent referral process in general practice and cancer services should accommodate patient perceptions and responses, facilitate referral and attendance, and enable responses to patient non-attendance., (© British Journal of General Practice 2019.)

Background: The 2-week-wait urgent referral policy in the UK has sought to improve cancer outcomes by accelerating diagnosis and treatment. However, around 5-7% of symptomatic referred patients cancel or do not attend their hospital appointment. While subsequent cancer diagnosis was less likely in non-attenders, those with a diagnosis had worse early mortality outcomes., Aim: To examine how interpersonal, communication, social, and organisational factors influence a patient's non-attendance., Design and Setting: Qualitative study in GP practices in one Northern English city., Method: In-depth, individual interviews were undertaken face-to-face or by telephone between December 2016 and May 2018, followed by thematic framework analysis., Results: In this study 21 GPs, and 24 patients who did not attend or had cancelled their appointment were interviewed, deriving a range of potential explanations for non-attendance, including: system flaws; GP difficulties with booking appointments; patient difficulties with navigating the appointment system, particularly older patients and those from more deprived areas; patients leading 'difficult lives'; and patients' expectations of the referral, informed by their beliefs, circumstances, priorities, and the perceived prognosis. GPs recognised the importance of communication with the patient, particularly the need to tailor communication to perceived patient understanding and anxiety. GPs and practices varied in their responses to patient non-attendance, influenced by time pressures and perceptions of patient responsibility., Conclusion: Failure to be seen within 2 weeks of urgent referral resulted from a number of patient and provider factors. The urgent referral process in general practice and cancer services should accommodate patient perceptions and responses, facilitate referral and attendance, and enable responses to patient non-attendance., (© British Journal of General Practice 2019.)

Background: Significant amounts of health data are stored as free-text within clinical reports, letters, discharge summaries and notes. Busy clinicians have limited time to read such large amounts of free-text and are at risk of information overload and consequently missing information vital to patient care. Automatically identifying relevant information at the point of care has the potential to reduce these risks but represents a considerable research challenge. One software solution that has been proposed in industry is the IBM Watson analytics suite which includes rule-based analytics capable of processing large document collections at scale., Results: In this paper we present an overview of IBM Watson Content Analytics and a feasibility study using Content Analytics with a large-scale corpus of clinical free-text reports within a UK National Health Service (NHS) context. We created dictionaries and rules for identifying positive incidence of hydronephrosis and brain metastasis from 5.6 m radiology reports and were able to achieve 94% precision, 95% recall and 89% precision, 94% recall respectively on a sample of manually annotated reports. With minor changes for US English we applied the same rule set to an open access corpus of 0.5 m radiology reports from a US hospital and achieved 93% precision, 94% recall and 84% precision, 88% recall respectively., Conclusions: We were able to implement IBM Watson within a UK NHS context and demonstrate effective results that could provide clinicians with an automatic safety net which highlights clinically important information within free-text documents. Our results suggest that currently available technologies such as IBM Watson Content Analytics already have the potential to address information overload and improve clinical safety and that solutions developed in one hospital and country may be transportable to different hospitals and countries. Our study was limited to exploring technical aspects of the feasibility of one industry solution and we recognise that healthcare text analytics research is a fast-moving field. That said, we believe our study suggests that text analytics is sufficiently advanced to be implemented within industry solutions that can improve clinical safety.

Background: Equations to estimate glomerular filtration rate based on serum creatinine are commonly used in cancer patients to assess renal function. However, there is uncertainty regarding which equation is most appropriate for this population and the impact of different creatinine assays., Methods: Measured isotopic glomerular filtration rate results from 120 oncology patients were used to evaluate and compare all four versions of the Wright equation, Cockcroft and Gault, Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology Collaboration and the Janowitz and Williams formula; using eight different creatinine assays (five Jaffe, three enzymatic)., Results: The enzymatic version of the Wright equation without creatine kinase performed better than the other versions for all eight creatinine assays. However, MDRD and Janowitz and Williams gave the best overall performance in this patient population. Performance was highly dependent on the creatinine assay used, for example, the percentage of results within 30% of the isotopic glomerular filtration rate (P30) ranged from 90.8% to 60.8% for MDRD., Conclusion: The performance of any equation to estimate glomerular filtration rate is highly dependent on the creatinine assay used. Oncology units should assess the performance of glomerular filtration rate equations using their laboratory creatinine assay to determine whether they can be used safely and effectively in cancer patients.

Introduction: Phase I of the Cancer Research UK Stratified Medicine Programme (SMP1) was designed to roll out molecular pathology testing nationwide at the point of cancer diagnosis, as well as facilitate an infrastructure where surplus cancer tissue could be used for research. It offered a non-trial setting to examine common UK cancer genetics in a real-world context., Methods: A total of 26 sites in England, Wales and Scotland, recruited samples from 7814 patients for genetic examination between 2011 and 2013. Tumour types involved were breast, colorectal, lung, prostate, ovarian cancer and malignant melanoma. Centralised molecular testing of surplus material from resections or biopsies of primary/metastatic tissue was performed, with samples examined for 3-5 genetic alterations deemed to be of key interest in site-specific cancers by the National Cancer Research Institute Clinical Study groups., Results: 10 754 patients (98% of those approached) consented to participate, from which 7814 tumour samples were genetically analysed. In total, 53% had at least one genetic aberration detected. From 1885 patients with lung cancer, KRAS mutation was noted to be highly prevalent in adenocarcinoma (37%). In breast cancer (1873 patients), there was a striking contrast in TP53 mutation incidence between patients with ductal cancer (27.3%) and lobular cancer (3.4%). Vast inter-tumour heterogeneity of colorectal cancer (1550 patients) was observed, including myriad double and triple combinations of genetic aberrations. Significant losses of important clinical information included smoking status in lung cancer and loss of distinction between low-grade and high-grade serous ovarian cancers., Conclusion: Nationwide molecular pathology testing in a non-trial setting is feasible. The experience with SMP1 has been used to inform ongoing CRUK flagship programmes such as the CRUK National Lung MATRIX trial and TRACERx., Competing Interests: Competing interests: Funding for the Stratified Medicine Programme is acknowledged from Cancer Research UK and programme founding partners AstraZeneca and Pfizer. For hosting the Stratified Medicine Programme data, thanks to the National Cancer Registration Service Eastern Office, Jim Davies and Steve Harris at the University of Oxford Department of Computer Science. AGN was supported by the National Institute of Health Research Respiratory Disease Biomedical Research Unit at the Royal Brompton and Harefield NHS Foundation Trust and Imperial College London. PJ, ES and CL have all been employed by Cancer Research UK in the past. FB was supported by Cancer Research UK Lung Cancer Centre of Excellence Funding. WAW was supported by Lothian NRS BioResource. SP acknowledges NHS funding to the NIHR Biomedical Research Centre at The Royal Marsden and the ICR. NPW was supported by Yorkshire Cancer Research. KGB was supported by a NHS Research Scotland Senior Fellowship.

The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.

Objectives: This study aimed to establish the association between timing and provision of palliative care (PC) and quality of end-of-life care indicators in a population of patients dying of cancer., Setting: This study uses linked cancer patient data from the National Cancer Registry, the electronic medical record system used in primary care (SystmOne) and the electronic medical record system used within a specialist regional cancer centre. The population resided in a single city in Northern England., Participants: Retrospective data from 2479 adult cancer decedents who died between January 2010 and February 2012 were registered with a primary care provider using the SystmOne electronic health record system, and cancer was certified as a cause of death, were included in the study., Results: Linkage yielded data on 2479 cancer decedents, with 64.5% who received at least one PC event. Decedents who received PC were significantly more likely to die in a hospice (39.4% vs 14.5%, P<0.005) and less likely to die in hospital (23.3% vs 40.1%, P<0.05), and were more likely to receive an opioid (53% vs 25.2%, P<0.001). PC initiated more than 2 weeks before death was associated with avoiding a hospital death (≥2 weeks, P<0.001), more than 4 weeks before death was associated with avoiding emergency hospital admissions and increased access to an opioid (≥4 weeks, P<0.001), and more than 33 weeks before death was associated with avoiding late chemotherapy (≥33 weeks, no chemotherapy P=0.019, chemotherapy over 4 weeks P=0.007)., Conclusion: For decedents with advanced cancer, access to PC and longer duration of PC were significantly associated with better end-of-life quality indicators., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Objectives: Use of point-of-care testing is increasing, however many haematology analysers can only determine granulocyte count without further differentiation into neutrophils, eosinophils and basophils. Since the diagnosis of life-threatening neutropenia in cancer patients requires a distinct neutrophil count, this study aimed to determine the comparative performance between the neutrophil and granulocyte count., Design and Methods: A database of 508 646 venous full blood count results measured on a laboratory reference analyser was mined from a large oncology unit. The relationship between granulocyte and neutrophil counts was assessed. Multinomial logistic regression was used to classify results into neutropenia grades using an equivalent granulocyte count., Results: Granulocyte to neutrophil count correlation was 0.997. The accuracy for classification into neutropenia grades using the derived equivalent granulocyte count ranges was 96.4%. Identification of results with a neutrophil count <1.5×10 9 cells/L using an equivalent granulocyte count of <1.69×10 9 cells/L resulted in sensitivity, specificity, positive and negative predictive values of 98.0%, 99.5%, 97.8% and 99.5%, respectively., Conclusions: These results describe the relationship between granulocyte and neutrophil counts, measured on a laboratory analyser, in a large population of patients with malignancies and receiving anti-cancer therapies. However, this relationship must be established using a point of care testing system with a three-part differential count before considering the possibility that a granulocyte count can guide clinical decisions in the absence of a definitive neutrophil count, to reduce the frequency and severity of neutropenic complications in patients receiving cancer treatments.

Background: There is growing interest in the use of routinely collected electronic health records to enhance service delivery and facilitate clinical research. It should be possible to detect and measure patterns of care and use the data to monitor improvements but there are methodological and data quality challenges. Driven by the desire to model the impact of a patient self-test blood count monitoring service in patients on chemotherapy, we aimed to (i) establish reproducible methods of process-mining electronic health records, (ii) use the outputs derived to define and quantify patient pathways during chemotherapy, and (iii) to gather robust data which is structured to be able to inform a cost-effectiveness decision model of home monitoring of neutropenic status during chemotherapy., Methods: Electronic Health Records at a UK oncology centre were included if they had (i) a diagnosis of metastatic breast cancer and received adjuvant epirubicin and cyclosphosphamide chemotherapy or (ii) colorectal cancer and received palliative oxaliplatin and infusional 5-fluorouracil chemotherapy, and (iii) were first diagnosed with cancer between January 2004 and February 2013. Software and a Markov model were developed, producing a schematic of patient pathways during chemotherapy., Results: Significant variance from the assumed care pathway was evident from the data. Of the 535 patients with breast cancer and 420 with colorectal cancer there were 474 and 329 pathway variants respectively. Only 27 (5%) and 26 (6%) completed the planned six cycles of chemotherapy without having unplanned hospital contact. Over the six cycles, 169 (31.6%) patients with breast cancer and 190 (45.2%) patients with colorectal cancer were admitted to hospital., Conclusion: The pathways of patients on chemotherapy are complex. An iterative approach to addressing semantic and data quality issues enabled the effective use of routinely collected patient records to produce accurate models of the real-life experiences of chemotherapy patients and generate clinically useful information. Very few patients experience the idealised patient pathway that is used to plan their care. A better understanding of real-life clinical pathways through process mining can contribute to care and data quality assurance, identifying unmet needs, facilitating quantification of innovation impact, communicating with stakeholders, and ultimately improving patient care and outcomes., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Symptom improvement in depression due to antidepressant treatment is highly variable and clinically unpredictable. Linking neuronal connectivity and genetic risk factors in predicting antidepressant response has clinical implications. Our investigation assessed whether indices of white matter integrity, serotonin transporter-linked polymorphism (5-HTTLPR) and brain-derived neurotrophic factor (BDNF) val66met polymorphism predicted magnitude of depression symptom change following antidepressant treatment. Fractional anisotropy (FA) was used as an indicator of white matter integrity and was assessed in the uncinate fasciculus and superior longitudinal fasciculus using tract-based spatial statistics (TBSS) and probabilistic tractography. Forty-six medication-free patients with major depressive disorder participated in a diffusion tensor imaging scan prior to completing an 8-week treatment regime with citalopram or quetiapine XR. Indexed improvements in Hamilton Depression Rating Scale score from baseline to 8-week endpoint were used as an indicator of depression improvement. Carriers of the BDNF met allele exhibited lower FA values in the left uncinate fasciculus relative to val/val individuals [F(1, 40) = 7.314, p = 0.009]. Probabilistic tractography identified that higher FA in the left uncinate fasciculus predicted percent change in depression severity, with BDNF moderating this association [F(3, 30) = 3.923, p = 0.018]. An interaction between FA in the right uncinate fasciculus and 5-HTTLPR also predicted percent change in depression severity [F(5, 25) = 5.315, p = 0.002]. Uncorrected TBSS results revealed significantly higher FA in hippocampal portions of the cingulum bundle in responders compared to non-responders (p = 0.016). The predictive value of prefrontal and amygdala/hippocampal WM connectivity on antidepressant treatment response may be influenced by 5-HTTLPR and BDNF polymorphisms in MDD.

Big datasets have the potential to revolutionize public health. However, there is a mismatch between the political and scientific optimism surrounding big data and the public's perception of its benefit. We suggest a systematic and concerted emphasis on developing models derived from smaller datasets to illustrate to the public how big data can produce tangible benefits in the long term. In order to highlight the immediate value of a small data approach, we produced a proof-of-concept model predicting hospital length of stay. The results demonstrate that existing small datasets can be used to create models that generate a reasonable prediction, facilitating health-care delivery. We propose that greater attention (and funding) needs to be directed toward the utilization of existing information resources in parallel with current efforts to create and exploit "big data."

Background: Rucaparib is an orally available potent selective small-molecule inhibitor of poly(ADP-ribose) polymerase (PARP) 1 and 2. Rucaparib induces synthetic lethality in cancer cells defective in the homologous recombination repair pathway including BRCA-1/2. We investigated the efficacy and safety of single-agent rucaparib in germline (g) BRCA mutation carriers with advanced breast and ovarian cancers., Methods: Phase II, open-label, multicentre trial of rucaparib in proven BRCA-1/2 mutation carriers with advanced breast and or ovarian cancer, WHO PS 0-1 and normal organ function. Intravenous (i.v.) and subsequently oral rucaparib were assessed, using a range of dosing schedules, to determine the safety, tolerability, dose-limiting toxic effects and pharmacodynamic (PD) and pharmacokinetic (PK) profiles., Results: Rucaparib was well tolerated in patients up to doses of 480 mg per day and is a potent inhibitor of PARP, with sustained inhibition ⩾24 h after single doses. The i.v. rucaparib (intermittent dosing schedule) resulted in an objective response rate (ORR) of only 2% but with 41% (18 out of 44) patients achieved stable disease for ⩾12 weeks and 3 patients maintaining disease stabilisation for >52 weeks. The ORR for oral rucaparib (across all six dose levels) was 15%. In the oral cohorts, 81% (22 out of 27) of the patients had ovarian cancer and 12 out of 13, who were dosed continuously, achieved RECIST complete response/partial response (CR/PR) or stable disease (SD) ⩾12 weeks, with a median duration of response of 179 days (range 84-567 days)., Conclusions: Rucaparib is well tolerated and results in high levels of PARP inhibition in surrogate tissues even at the lowest dose levels. Rucaparib is active in gBRCA-mutant ovarian cancer and this activity correlates with platinum-free interval. The key lessons learned from this study is that continuous rucaparib dosing is required for optimal response, the recommended phase 2 dose (RP2D) for continuous oral scheduling has not been established and requires further exploration and, thirdly, the use of a PD biomarker to evaluate dose-response has its limitations.

The Association of Cancer Physicians in the United Kingdom has developed a strategy to improve outcomes for cancer patients and identified the goals and commitments of the Association and its members.

Background: 30-day mortality (30DM) has been suggested as a clinical indicator of the avoidance of harm in palliative radiotherapy within the NHS, but no large-scale population-based studies exist. This large retrospective cohort study aims to investigate the factors that influence 30DM following palliative radiotherapy and consider its value as a clinical indicator., Methods: All radiotherapy episodes delivered in a large UK cancer centre between January 2004 and April 2011 were analysed. Patterns of palliative radiotherapy, 30DM and the variables affecting 30DM were assessed. The impact of these variables was assessed using logistic regression., Results: 14,972 palliative episodes were analysed. 6334 (42.3%) treatments were delivered to bone metastases, 2356 (15 7%) to the chest for lung cancer and 915 (5.7%) to the brain. Median treatment time was 1day (IQR 1-7). Overall 30DM was 12.3%. Factors having a significant impact upon 30DM were sex, primary diagnosis, treatment site and fractionation schedule (p<0.01)., Conclusion: This is the first large-scale description of 30-day mortality for unselected adult palliative radiotherapy treatments. The observed differences in early mortality by fractionation support the use of this measure in assessing clinical decision making in palliative radiotherapy and require further study in other centres and health care systems., (Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.)

The arrival of personalized medicine in the clinic means that treatment decisions will increasingly rely on test results. The challenge of limited healthcare resources means that the dissemination of these technologies will be dependent on their value in relation to their cost, i.e., their cost effectiveness. Phelps and Mushlin have described how to optimize tests to meet a cost-effectiveness target. However, when tests are applied repeatedly the case mix of the patients tested changes with each administration, and this impacts upon the value of each subsequent test administration. In this article, we present a modification of Phelps and Mushlin's framework for diagnostic tests; to identify the cost-effective cut-off for monitoring tests. Using the Ca125 test monitoring for relapse in ovarian cancer, we show how the repeated use of the initial cut-off can lead to a substantially increased false-negative rate compared with the monitoring cut-off-over 4% higher than in this example-with the associated harms for individual and population health.

Purpose: Reovirus type 3 Dearing (RT3D) replicates preferentially in Ras-activated cancers. RT3D shows synergistic in vitro cytotoxicity in combination with platins and taxanes. The purpose of this phase I/II study was to assess RT3D combined with carboplatin/paclitaxel in patients with advanced cancers., Experimental Design: Patients were initially treated in a dose-escalating, phase I trial with intravenous RT3D days 1 to 5, carboplatin [area under curve (AUC) 5, day 1] and paclitaxel (175 mg/m(2), day 1) 3-weekly. RT3D was escalated through three dose levels: 3 × 10(9), 1 × 10(10), and 3 × 10(10) TCID(50) in cohorts of three. Primary endpoints were to define the maximum tolerated dose and dose-limiting toxicity and to recommend a dose for phase II studies. Secondary endpoints included pharmacokinetics, immune response, and antitumor activity. A subsequent phase II study using the 3 × 10(10) TCID(50) dose characterized the response rate in patients with head and neck cancer., Results: Thirty-one heavily pretreated patients received study therapy. There were no dose-limiting toxicities during dose-escalation and most toxicities were grade I/II. Overall effectiveness rates were as follows: one patient had a complete response (3.8%), six patients (23.1%) had partial response, two patients (7.6%) had major clinical responses clinically evaluated in radiation pretreated lesions which are not evaluable by Response Evaluation Criteria in Solid Tumors (RECIST), nine patients (34.6%) had stable disease, and eight patients (30.8%) had disease progression. Viral shedding was minimal and antiviral immune responses were attenuated compared with previous single-agent data for RT3D., Conclusions: The combination of RT3D plus carboplatin/paclitaxel is well tolerated with evidence of activity in cancer of the head and neck. A randomized phase III study is currently open for recruitment., (©2012 AACR.)

Highly aneuploid tumours are common in epithelial ovarian cancers (EOC). We investigated whether NuMA expression was associated with this phenomenon.NuMA protein levels in normal and tumour tissues, ovarian cell lines and primary cultures of malignant cells derived from ovarian ascitic fluids were analysed by Affymetrix microarray analysis, immunoblotting, immunohistochemistry (IHC) and immunofluorescence (IF), with results correlated to associated clinical data. Aneuploidy status in primary cultures was determined by FACS analysis.Affymetrix microarray data indicated that NuMA was overexpressed in tumour tissue, primary cultures and cell lines compared to normal ovarian tissue. IHC revealed low to weak NuMA expression in normal tissues. Expression was upregulated in tumours, with a significant association with disease stage in mucinous EOC subtypes (p = 0.009), lymph node involvement (p = 0.03) and patient age (p = 0.04). Additional discontinuous data analysis revealed that high NuMA levels in tumours decreased with grade (p = 0.02) but increased with disease stage (p = 0.04) in serous EOC. NuMA expression decreased in late disease stage 4 endometrioid EOCs. High NuMA levels decreased with increased tumour invasion in all subtypes (p = 0.03). IF of primary cultures revealed that high NuMA levels at mitotic spindle poles were significantly associated with a decreased proportion of cells in cytokinesis (p = 0.05), increased binucleation (p = 0.021) and multinucleation (p = 0.007), and aneuploidy (p = 0.008).NuMA is highly expressed in EOC tumours and high NuMA levels correlate with increases in mitotic defects and aneuploidy in primary cultures.

Secondary use of patient databases is essential in healthcare if clinical trials are to progress efficiently to planned time and target and imperative if the planned UK expansion of research and development (R&D) at point of care is to be achieved. Integration of effective databases primarily designed to facilitate patient care with R&D requirements is needed but represents a complex challenge. We present a system that achieves an integrated approach with online management of complex datasets for clinical trials within care records using a specific study as an example to show functionality in practice; illustrating how this system provides an ideal resource to meet the needs of both clinicians and researchers., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Purpose: To assess the significance of CA-125 regression as a prognostic indicator and predictor of optimal cytoreduction at interval debulking surgery (IDS) in women with ovarian or primary peritoneal carcinoma receiving neoadjuvant chemotherapy (NAC)., Methods: 63 women treated between 2004 and 2007 with neoadjuvant platinum-based chemotherapy followed by IDS were studied retrospectively. Pre-operative CA-125 values were used to calculate a regression coefficient (CA-125r) using exponential regression analysis. Outcome endpoints were overall survival (OS), time to CA-125 progression (TTC) by Rustin criteria and time to second-line treatment (TTS)., Results: Women with a CA-125 half-life greater than 18 days had a significantly worse OS compared to those with a half-life less than 12 days on univariate testing (HR 3.34, 95% CI 1.25-8.94, p = 0.017). On multivariable analysis, CA-125r was an independent predictor of OS [HR 1.18 (per 0.01 increase in CA-125r), 95% CI 1.01-1.40, p = 0.043]. CA-125r was independently predictive of TTC and TTS (HR 1.17, p ≈ 0.03 for each). CA-125r was also predictive of achieving optimal cytoreduction at IDS (AUC 0.756, p < 0.001)., Conclusions: CA-125 regression rate during pre-operative NAC is of independent prognostic value. CA-125 regression rate strongly predicts for optimal cytoreduction.

The NeuroDevNet Autism Spectrum Disorder Demonstration Project interfaces at many levels with the network's research themes and priorities. Our interdisciplinary team aims to improve understanding of genetic factors underlying vulnerability to autism spectrum disorders (ASDs) to develop better diagnostic strategies and, ultimately, to pinpoint molecular pathways relevant to developing biologically based treatments. Linking our existing longitudinal ASD cohorts with both genetics and neuroimaging studies will provide, for the first time, integrated data on how the genetic variation influences brain and behavioral development in ASD. Importantly, as our science progresses and we translate this information to the health care system, we will also educate policy makers, media, and business, so an informed society is prepared to capitalize on new genomic advances and effectively integrate these into health services for the broader community. We believe that this research has the potential to transform assessment and care for individuals with ASD., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Clinical trials of oncolytic virotherapy have shown low toxicity and encouraging signs of efficacy. However, it remains critically important to develop methods for systemic viral delivery if such therapies are to be clinically implemented to treat established tumors. In this respect, much effort is being focused on combining oncolytic viruses with standard treatment modalities such as inhibitors of VEGF165 (an alternatively spliced isoform of VEGF-A) signaling, which are widely used to treat several different cancers. Here, we have demonstrated that combining VEGF165 inhibitors with systemic delivery of oncolytic viruses leads to substantial regression and cure of established tumors in immunocompetent mice. We have shown that manipulating VEGF165-mediated signaling by administering VEGF165 to mice harboring mouse melanoma cells that do not express VEGF165 and by administering a VEGF inhibitor and then withdrawing treatment to allow VEGF levels to rebound in mice harboring mouse melanoma cells expressing VEGF165 allows tumor-associated endothelial cells transiently to support viral replication. This approach led to direct tumor cell lysis and triggered innate immune-mediated attack on the tumor vasculature. It also resulted in long-term antitumor effects, even against tumors in which viral replication is poorly supported. Since this combinatorial approach targets the tumor endothelium, we believe these data have direct, wide-ranging, and immediate clinical applicability across a broad range of tumor types.

There are several roadblocks that hinder systemic delivery of oncolytic viruses to the sites of metastatic disease. These include the tumor vasculature, which provides a physical barrier to tumor-specific virus extravasation. Although interleukin-2 (IL-2) has been used in antitumor therapy, it is associated with endothelial cell injury, leading to vascular leak syndrome (VLS). Here, we demonstrate that IL-2-mediated VLS, accentuated by depletion of regulatory T cells (Treg), facilitates localization of intravenously (i.v.) delivered oncolytic virus into established tumors in immune-competent mice. IL-2, in association with Treg depletion, generates "hyperactivated" natural killer (NK) cells, possessing antitumor activity and secreting factors that facilitate virus spread/replication throughout the tumor by disrupting the tumor architecture. As a result, the combination of Treg depletion/IL-2 and systemic oncolytic virotherapy was found to be significantly more therapeutic against established disease than either treatment alone. These data demonstrate that it is possible to combine biological therapy with oncolytic virotherapy to generate systemic therapy against established tumors.

There are several roadblocks that hinder systemic delivery of oncolytic viruses to the sites of metastatic disease. These include the tumor vasculature, which provides a physical barrier to tumor-specific virus extravasation. Although interleukin-2 (IL-2) has been used in antitumor therapy, it is associated with endothelial cell injury, leading to vascular leak syndrome (VLS). Here, we demonstrate that IL-2-mediated VLS, accentuated by depletion of regulatory T cells (Treg), facilitates localization of intravenously (IV) delivered oncolytic virus into established tumors in immune-competent mice. IL-2, in association with Treg depletion, generates "hyperactivated" natural killer (NK) cells, possessing antitumor activity and secreting factors that facilitate virus spread/replication throughout the tumor by disrupting the tumor architecture. As a result, the combination of Treg depletion/IL-2 and systemic oncolytic virotherapy was found to be significantly more therapeutic against established disease than either treatment alone. These data demonstrate that it is possible to combine biological therapy with oncolytic virotherapy to generate systemic therapy against established tumors., (Copyright © 2008 The American Society of Gene Therapy. Published by Elsevier Inc. All rights reserved.)

Epithelial ovarian cancer (EOC) remains a major source of cancer morbidity and mortality, despite advances in surgical and chemotherapeutic management. The molecular pathways that control angiogenesis have been demonstrated to be key to the pathogenesis of EOC, and have been shown to have prognostic significance. Increased understanding of the pathways and molecules involved in angiogenesis has allowed the identification of a number of targets for antiangiogenic therapies and the development of a variety of antiangiogenic drugs. There is now significant preclinical evidence, and a growing body of clinical data, demonstrating promising results with antiangiogenic drugs in the treatment of EOC. Single-agent VEGF inhibitor response rates in pretreated patients of between 15 and 20% have been reported, with much higher response rates when used in combination with chemotherapeutic agents. These benefits, however, must be balanced with the toxicities associated with these drugs, particularly the more serious ones, such as gastrointestinal perforation. The results of ongoing and future randomized clinical trials will confirm if, and how, antiangiogenic therapies should be integrated into the routine management of EOC. However, critical issues, such as the relative importance of combination remission induction regimens and maintenance therapy, remain poorly defined.

Objective: Using a Delphi Consultation process, a group of medical writers established by the European Medical Writers Association (EMWA) set out to determine the current thinking on the problems of ghostwriting in medical publications and what should be done about them. In this context, ghostwriting is where a professional medical writer prepares a manuscript on behalf of a named author, but the writer is not listed as an author., Methods: A 4-round Delphi consultation process was conducted via email to generate statements about the main issues in ghostwriting. Participants rated their agreement with the statements on a scale of 0-10., Results and Conclusions: Members of the task force strongly believed that professional medical writers can improve the quality of scientific papers, but that fact is often not recognised outside the medical writing profession. At least in part, this is because of a perception that ghostwritten papers may have been inappropriately influenced by pharmaceutical companies. One theme that emerged strongly from the discussions was transparency. Members thought it very important that the existence of a ghostwriter should always be made clear to the reader. Another strong theme was the importance of defining in detail what practices relating to ghostwriting are ethical, and what practices are not. This definition of ethical ghostwriting should be widely known, and unethical ghostwriting should be strongly condemned. Use of the term 'ghostwriting' itself was questioned. Members of the task force felt that use of a more neutral term should be encouraged. The task force suggested various activities for ensuring that above the objectives could be met, including discussions with other interested parties, such as journal editors and pharmaceutical companies, educating medical writers about ethical practices, further research into ghostwriting, and developing guidelines for ethical medical writing.