How often do cancer researchers make their data and code available and what factors are associated with sharing?

BACKGROUND: Various stakeholders are calling for increased availability of data and code from cancer research. However, it is unclear how commonly these products are shared, and what factors are associated with sharing. Our objective was to evaluate how frequently oncology researchers make data and code available and explore factors associated with sharing. METHODS: A cross-sectional analysis of a random sample of 306 cancer-related articles indexed in PubMed in 2019 which studied research subjects with a cancer diagnosis was performed. All articles were independently screened for eligibility by two authors. Outcomes of interest included the prevalence of affirmative sharing declarations and the rate with which declarations connected to data complying with key FAIR principles (e.g. posted to a recognised repository, assigned an identifier, data license outlined, non-proprietary formatting). We also investigated associations between sharing rates and several journal characteristics (e.g. sharing policies, publication models), study characteristics (e.g. cancer rarity, study design), open science practices (e.g. pre-registration, pre-printing) and subsequent citation rates between 2020 and 2021. RESULTS: One in five studies declared data were publicly available (59/306, 19%, 95% CI: 15-24%). However, when data availability was investigated this percentage dropped to 16% (49/306, 95% CI: 12-20%), and then to less than 1% (1/306, 95% CI: 0-2%) when data were checked for compliance with key FAIR principles. While only 4% of articles that used inferential statistics reported code to be available (10/274, 95% CI: 2-6%), the odds of reporting code to be available were 5.6 times higher for researchers who shared data. Compliance with mandatory data and code sharing policies was observed in 48% (14/29) and 0% (0/6) of articles, respectively. However, 88% of articles (45/51) included data availability statements when required. Policies that encouraged data sharing did not appear to be any more effective than not having a policy at all. The only factors associated with higher rates of data sharing were studying rare cancers and using publicly available data to complement original research. CONCLUSIONS: Data and code sharing in oncology occurs infrequently, and at a lower rate than would be expected given the prevalence of mandatory sharing policies. There is also a large gap between those declaring data to be available, and those archiving data in a way that facilitates its reuse. We encourage journals to actively check compliance with sharing policies, and researchers consult community-accepted guidelines when archiving the products of their research.

PET-detected pneumonitis following curative-intent chemoradiation in non-small cell lung cancer (NSCLC): recognizing patterns and assessing the impact on the predictive ability of FDG-PET/CT response assessment.

PURPOSE: Inflammatory FDG uptake in the lung (PET-pneumonitis) following curative-intent radiotherapy (RT)/chemo-RT (CRT) in non-small cell lung cancer (NSCLC) can pose a challenge in FDG-PET/CT response assessment. The aim of this study is to describe different patterns of PET-pneumonitis to guide the interpretation of FDG-PET/CT and investigate its association with tumor response and overall survival (OS). METHODS: Retrospective analysis was performed on 87 NSCLC patients in three prospective trials who were treated with radical RT (n = 7) or CRT (n = 80), with baseline and post-treatment FDG-PET/CT. Visual criteria were performed for post-treatment FDG-PET/CT response assessment. The grading of PET-pneumonitis was based on relative lung uptake intensity compared to organs of reference and classified as per Deauville score from grade 1-5. Distribution patterns of PET-pneumonitis were defined as follows: A) patchy/sub-pleural; B) diffuse (involving more than a segment); and C) peripheral (diffusely surrounding a photopenic region). RESULTS: Follow-up FDG-PET/CT scans were performed approximately 3 months (median, 89 days; interquartile range, 79-93) after RT. Overall, PET-pneumonitis was present in 62/87 (71%) of patients, with Deauville 2 or 3 in 12/62 (19%) and 4 or 5 in 50/62 (81%) of patients. The frequency of patterns A, B and C of PET-pneumonitis was 19/62 (31%), 20/62 (32%) and 23/62 (37%), respectively. No association was found between grade or pattern of PET-pneumonitis and overall response at follow-up PET/CT (p = 0.27 and p = 0.56, respectively). There was also no significant association between PET-pneumonitis and OS (hazard ratio [HR], 1.3; 95% confidence interval [CI], 0.6-2.5; p = 0.45). Early FDG-PET/CT response assessment, however, was prognostic for OS (HR, 1.7; 95% CI, 1.2-2.2; p < 0.001). CONCLUSION: PET-pneumonitis is common in early post-CRT/RT, but pattern recognition may assist in response assessment by FDG-PET/CT. While FDG-PET/CT is a powerful tool for response assessment and prognostication, PET-pneumonitis does not appear to confound early response assessment or to independently predict OS.

Early Skeletal Muscle Loss in Non-Small Cell Lung Cancer Patients Receiving Chemoradiation and Relationship to Survival.

PURPOSE: Sarcopenia is associated with reduced survival in cancer. Currently, data on sarcopenia at presentation and muscle loss throughout treatment are unknown in patients receiving chemoradiation therapy (CRT) for non-small cell lung cancer (NSCLC). This study evaluated skeletal muscle changes in NSCLC patients receiving CRT and relationship with survival. METHODS: Secondary analysis of 41 patients with NSCLC treated with CRT assessed for skeletal muscle area and muscle density by computed tomography pre-treatment and 3 months post-treatment. Images at week 4 of treatment were available for 32 (78%) patients. Linear mixed models were applied to determine changes in skeletal muscle over time and related to overall survival using Kaplan-Meier plots. RESULTS: Muscle area and muscle density decreased significantly by week 4 of CRT (- 6.6 cm2, 95% CI - 9.7 to - 3.1, p < 0.001; - 1.3 HU, 95% CI - 1.9 to - 0.64, p < 0.001, respectively), with minimal change between week 4 of CRT and 3 months post-CRT follow-up (- 0.2 cm2, 95% CI - 3.6-3.1, p = 0.91; - 0.27, 95% CI - 0.91-0.36, p = 0.36, respectively). Sarcopenia was present in 25 (61%) and sarcopenic obesity in 6 (14%) of patients prior to CRT, but not associated with poorer survival. Median survival was shorter in patients with low muscle density prior to treatment although not statistically significant (25 months + 8.3 vs 53 months + 13.0, log-rank p = 0.17). CONCLUSION: Significant loss of muscle area and muscle density occurs in NSCLC patients early during CRT. A high proportion of patients are sarcopenic prior to CRT; however, this was not significantly associated with poorer survival.

What do Australians affected by cancer think about oncology researchers sharing research data? A cross-sectional survey.

AIM: Previous research has shown patients and the public in Australia generally support medical researchers in making de-identified research data available to other scientists. However, this research has focussed on certain types of data and recipients. We surveyed Australians affected by cancer to characterize their attitudes toward the sharing of research data with multiple third parties, including the public. METHODS: A short, anonymous online survey of Australians with a previous diagnosis of cancer was advertised between October 27, 2022, and February 27, 2023. Quantitative responses were analyzed with descriptive statistics. Free-text responses were coded deductively and summarised using content analysis. RESULTS: In total, 551 respondents contributed data to the survey. There was strong support for cancer researchers sharing non-human and de-identified human research data with clinicians (90% and 95%, respectively) and non-profit researchers (both 94%). However, fewer participants supported sharing data with for-profit researchers (both 64%) or publicly (both 61%). When asked if they would hypothetically consent to researchers at their treatment location using and sharing their de-identified data publicly, only half agreed. In contrast, after being shown a visual representation of the de-identified survey data, 80% of respondents supported sharing it publicly. CONCLUSION: Australians affected by cancer support the sharing of research data, particularly with clinicians and non-profit researchers. Our results also imply that visualization of the data to be shared may enhance support for making it publicly available. These results should help alleviate any concerns about research participants' attitudes toward data sharing, as well as boost researchers' motivation for sharing.

Cancer researchers' experiences with and perceptions of research data sharing: Results of a cross-sectional survey.

BACKGROUND: Despite wide recognition of the benefits of sharing research data, public availability rates have not increased substantially in oncology or medicine more broadly over the last decade. METHODS: We surveyed 285 cancer researchers to determine their prior experience with sharing data and views on known drivers and inhibitors. RESULTS: We found that 45% of respondents had shared some data from their most recent empirical publication, with respondents who typically studied non-human research participants, or routinely worked with human genomic data, more likely to share than those who did not. A third of respondents added that they had previously shared data privately, with 74% indicating that doing so had also led to authorship opportunities or future collaborations for them. Journal and funder policies were reported to be the biggest general drivers toward sharing, whereas commercial interests, agreements with industrial sponsors and institutional policies were the biggest prohibitors. We show that researchers' decisions about whether to share data are also likely to be influenced by participants' desires. CONCLUSIONS: Our survey suggests that increased promotion and support by research institutions, alongside greater championing of data sharing by journals and funders, may motivate more researchers in oncology to share their data.

An epithelial-to-mesenchymal transition induced extracellular vesicle prognostic signature in non-small cell lung cancer.

Despite significant therapeutic advances, lung cancer remains the leading cause of cancer-related death worldwide1. Non-small cell lung cancer (NSCLC) patients have a very poor overall five-year survival rate of only 10-20%. Currently, TNM staging is the gold standard for predicting overall survival and selecting optimal initial treatment options for NSCLC patients, including those with curable stages of disease. However, many patients with locoregionally-confined NSCLC relapse and die despite curative-intent interventions, indicating a need for intensified, individualised therapies. Epithelial-to-mesenchymal transition (EMT), the phenotypic depolarisation of epithelial cells to elongated, mesenchymal cells, is associated with metastatic and treatment-refractive cancer. We demonstrate here that EMT-induced protein changes in small extracellular vesicles are detectable in NSCLC patients and have prognostic significance. Overall, this work describes a novel prognostic biomarker signature that identifies potentially-curable NSCLC patients at risk of developing metastatic NSCLC, thereby enabling implementation of personalised treatment decisions.

Please Place Your Seat in the Full Upright Position: A Technical Framework for Landing Upright Radiation Therapy in the 21st Century.

Delivering radiotherapy to patients in an upright position can allow for increased patient comfort, reduction in normal tissue irradiation, or reduction of machine size and complexity. This paper gives an overview of the requirements for the delivery of contemporary arc and modulated radiation therapy to upright patients. We explore i) patient positioning and immobilization, ii) simulation imaging, iii) treatment planning and iv) online setup and image guidance. Treatment chairs have been designed to reproducibly position seated patients for treatment and can be augmented by several existing immobilisation systems or promising emerging technologies such as soft robotics. There are few solutions for acquiring CT images for upright patients, however, cone beam computed tomography (CBCT) scans of upright patients can be produced using the imaging capabilities of standard Linacs combined with an additional patient rotation device. While these images will require corrections to make them appropriate for treatment planning, several methods indicate the viability of this approach. Treatment planning is largely unchanged apart from translating gantry rotation to patient rotation, allowing for a fixed beam with a patient rotating relative to it. Rotation can be provided by a turntable during treatment delivery. Imaging the patient with the same machinery as used in treatment could be advantageous for online plan adaption. While the current focus is using clinical linacs in existing facilities, developments in this area could also extend to lower-cost and mobile linacs and heavy ion therapy.

Imaging immunity in patients with cancer using positron emission tomography.

Immune checkpoint inhibitors and related molecules can achieve tumour regression, and even prolonged survival, for a subset of cancer patients with an otherwise dire prognosis. However, it remains unclear why some patients respond to immunotherapy and others do not. PET imaging has the potential to characterise the spatial and temporal heterogeneity of both immunotherapy target molecules and the tumor immune microenvironment, suggesting a tantalising vision of personally-adapted immunomodulatory treatment regimens. Personalised combinations of immunotherapy with local therapies and other systemic therapies, would be informed by immune imaging and subsequently modified in accordance with therapeutically induced immune environmental changes. An ideal PET imaging biomarker would facilitate the choice of initial therapy and would permit sequential imaging in time-frames that could provide actionable information to guide subsequent therapy. Such imaging should provide either prognostic or predictive measures of responsiveness relevant to key immunotherapy types but, most importantly, guide key decisions on initiation, continuation, change or cessation of treatment to reduce the cost and morbidity of treatment while enhancing survival outcomes. We survey the current literature, focusing on clinically relevant immune checkpoint immunotherapies, for which novel PET tracers are being developed, and discuss what steps are needed to make this vision a reality.

Blood-Derived Extracellular Vesicle-Associated miR-3182 Detects Non-Small Cell Lung Cancer Patients.

With five-year survival rates as low as 3%, lung cancer is the most common cause of cancer-related mortality worldwide. The severity of the disease at presentation is accredited to the lack of early detection capacities, resulting in the reliance on low-throughput diagnostic measures, such as tissue biopsy and imaging. Interest in the development and use of liquid biopsies has risen, due to non-invasive sample collection, and the depth of information it can provide on a disease. Small extracellular vesicles (sEVs) as viable liquid biopsies are of particular interest due to their potential as cancer biomarkers. To validate the use of sEVs as cancer biomarkers, we characterised cancer sEVs using miRNA sequencing analysis. We found that miRNA-3182 was highly enriched in sEVs derived from the blood of patients with invasive breast carcinoma and NSCLC. The enrichment of sEV miR-3182 was confirmed in oncogenic, transformed lung cells in comparison to isogenic, untransformed lung cells. Most importantly, miR-3182 can successfully distinguish early-stage NSCLC patients from those with benign lung conditions. Therefore, miR-3182 provides potential to be used for the detection of NSCLC in blood samples, which could result in earlier therapy and thus improved outcomes and survival for patients.

Nodal metabolic tumour volume on baseline 18 F-FDG PET/CT and overall survival in stage II and III NSCLC patients undergoing curative-intent chemoradiotherapy/radiotherapy.

INTRODUCTION: This study aims to investigate whether nodal metabolic tumour volume (nMTV) and nodal total lesion glycolysis (nTLG) on Fluorine-18 fluoro-deoxy-glucose positron emission tomography-computed tomography (18 F-FDG PET/CT) in inoperable node-positive stage II and III non-small cell lung cancer (NSCLC) are independent predictors of overall survival (OS) in patients undergoing curative-intent chemoradiotherapy/radiotherapy (CRT/RT). METHODS: Data from two prospective trials between 2004 and 2016 were analysed retrospectively. Primary, nodal and total metabolic tumour volume and total lesion glycolysis (pMTV, nMTV, tMTV, pTLG, nTLG and tTLG, respectively) were derived from baseline 18 F-FDG PET/CT. Cox regressions were used to model OS by 18 F-FDG PET/CT parameters adjusting for overall stage. RESULTS: 89 patients with stage II (8%) and stage III (92%) were included. The median age at diagnosis was 67 years; 62% were male. The median follow-up was 6.9 years; the median OS was 2.2 years (95% CI 1.7-3.1). The median pMTV, nMTV and tMTV were 14 mL (range 0-360), 8 mL (range 0-250) and 34 mL (range 3-384), respectively. In 3 patients, the primary lesion could not be delineated from the central hilar mass. There was no association between nMTV (adjusted HR 1.04, 95% CI 0.95-1.15, P-value 0.43), pMTV (adjusted HR 1.0, 95% CI 0.96-1.04, P-value 0.92), tMTV (adjusted HR 1.0, 95% CI 0.97-1.04, P-value 0.88), nTLG, pTLG or tTLG and OS. Consistent results were noted when patients with central hilar lesions were excluded from analysis. CONCLUSION: In node-positive stage II and III NSCLC patients who underwent 18 F-FDG PET/CT-guided target delineation curative-intent concurrent CRT/RT, metabolic parameters did not appear to provide independent prognostication.

A Deep Learning Model to Automate Skeletal Muscle Area Measurement on Computed Tomography Images.

BACKGROUND: Muscle wasting (Sarcopenia) is associated with poor outcomes in cancer patients. Early identification of sarcopenia can facilitate nutritional and exercise intervention. Cross-sectional skeletal muscle (SM) area at the third lumbar vertebra (L3) slice of a computed tomography (CT) image is increasingly used to assess body composition and calculate SM index (SMI), a validated surrogate marker for sarcopenia in cancer. Manual segmentation of SM requires multiple steps, which limits use in routine clinical practice. This project aims to develop an automatic method to segment L3 muscle in CT scans. METHODS: Attenuation correction CTs from full body PET-CT scans from patients enrolled in two prospective trials were used. The training set consisted of 66 non-small cell lung cancer (NSCLC) patients who underwent curative intent radiotherapy. An additional 42 NSCLC patients prescribed curative intent chemo-radiotherapy from a second trial were used for testing. Each patient had multiple CT scans taken at different time points prior to and post- treatment (147 CTs in the training and validation set and 116 CTs in the independent testing set). Skeletal muscle at L3 vertebra was manually segmented by two observers, according to the Alberta protocol to serve as ground truth labels. This included 40 images segmented by both observers to measure inter-observer variation. An ensemble of 2.5D fully convolutional neural networks (U-Nets) was used to perform the segmentation. The final layer of U-Net produced the binary classification of the pixels into muscle and non-muscle area. The model performance was calculated using Dice score and absolute percentage error (APE) in skeletal muscle area between manual and automated contours. RESULTS: We trained five 2.5D U-Nets using 5-fold cross validation and used them to predict the contours in the testing set. The model achieved a mean Dice score of 0.92 and an APE of 3.1% on the independent testing set. This was similar to inter-observer variation of 0.96 and 2.9% for mean Dice and APE respectively. We further quantified the performance of sarcopenia classification using computer generated skeletal muscle area. To meet a clinical diagnosis of sarcopenia based on Alberta protocol the model achieved a sensitivity of 84% and a specificity of 95%. CONCLUSIONS: This work demonstrates an automated method for accurate and reproducible segmentation of skeletal muscle area at L3. This is an efficient tool for large scale or routine computation of skeletal muscle area in cancer patients which may have applications on low quality CTs acquired as part of PET/CT studies for staging and surveillance of patients with cancer.

Predicting muscle loss during lung cancer treatment (PREDICT): protocol for a mixed methods prospective study.

INTRODUCTION: Low muscle mass and low muscle attenuation (radiodensity), reflecting increased muscle adiposity, are prevalent muscle abnormalities in people with lung cancer receiving curative intent chemoradiation therapy (CRT) or radiation therapy (RT). Currently, there is a limited understanding of the magnitude, determinants and clinical significance of these muscle abnormalities in the lung cancer CRT/RT population. The primary objective of this study is to identify the predictors of muscle abnormalities (low muscle mass and muscle attenuation) and their depletion over time in people with lung cancer receiving CRT/RT. Secondary objectives are to assess the magnitude of change in these parameters and their association with health-related quality of life, treatment completion, toxicities and survival. METHODS AND ANALYSIS: Patients diagnosed with lung cancer and planned for treatment with CRT/RT are invited to participate in this prospective observational study, with a target of 120 participants. The impact and predictors of muscle abnormalities (assessed via CT at the third lumbar vertebra) prior to and 2 months post CRT/RT on the severity of treatment toxicities, treatment completion and survival will be assessed by examining the following variables: demographic and clinical factors, weight loss, malnutrition, muscle strength, physical performance, energy and protein intake, physical activity and sedentary time, risk of sarcopenia (Strength, Assistance in walking, Rise from a chair, Climb stairs, Falls history (SARC-F) score alone and with calf-circumference) and systemic inflammation. A sample of purposively selected participants with muscle abnormalities will be invited to take part in semistructured interviews to understand their ability to cope with treatment and explore preference for treatment strategies focused on nutrition and exercise. ETHICS AND DISSEMINATION: The PREDICT study received ethics approval from the Human Research Ethics Committee at Peter MacCallum Cancer Centre (HREC/53147/PMCC-2019) and Deakin University (2019-320). Findings will be disseminated through peer review publications and conference presentations.

Non-small cell lung cancer stage migration as a function of wait times from diagnostic imaging: A pooled analysis from five international centres.

INTRODUCTION: Patients with non-small cell lung cancer (NSCLC) can experience rapid disease progression between initial staging FDG-PET scans and commencement of curative-intent radiotherapy (RT). Previous studies that estimated stage migration rates by comparing staging PET/CT and treatment-planning PET/CT images were limited by small sample sizes. METHODS: This multicenter, international study combined prospective data from five institutions for PET-staged patients with NSCLC who were intended to receive curative-intent RT. TNM status was compared for staging and RT planning scans and the probability of TNM status and overall stage migration was analyzed as a function of the interval between PET/CT scans. The impacts of N classification, overall stage, and pathology were also studied. RESULTS: Pooled data from 181 patients were analyzed. The median interval between PET/CT scans was 42 days (range, 2-208). Upstaging occurred in 32 % of patients. The overall rate of stage migration was higher for patients presenting with initial stage IIIB/IIIC disease (p = 0.006) and patients with N2-3 nodal disease (p = 0.019). Upstaging to M1 disease was significantly associated with initial stage IIIB/IIIC disease (HR = 15.2) and adenocarcinoma (HR = 10) histology. CONCLUSION: Longer intervals between imaging and treatment in patients with NSCLC were associated with high rates disease progression with consequent risks of geographic miss in RT planning and futile treatment in patients with M1 disease. Patients with more extensive initial nodal involvement and those with adenocarcinoma had the highest rates of stage migration. Dedicated RT planning PET/CT imaging is recommended, especially if >3 weeks have elapsed after initial staging.

Characterizing the Heterogeneity of Small Extracellular Vesicle Populations in Multiple Cancer Types via an Ultrasensitive Chip.

Identifying small extracellular vesicle (sEV) subpopulations based on their different molecular signatures could potentially reveal the functional roles in physiology and pathology. However, it is a challenge to achieve this aim due to the nano-sized dimensions of sEVs, low quantities of biological cargo each sEV carries, and our incomplete knowledge of identifying features capable of separating heterogeneous sEV subpopulations. Here, a sensitive, multiplexed, and nano-mixing-enhanced sEV subpopulation characterization platform (ESCP) is proposed to precisely determine the sEV phenotypic heterogeneity and understand the role of sEV heterogeneity in cancer progression and metastasis. The ESCP utilizes spatially patterned anti-tetraspanin-functionalized micro-arrays for sEV subpopulation sorting and nanobarcode-based surface-enhanced Raman spectroscopy for multiplexed read-outs. An ESCP has been used for investigating sEV phenotypic heterogeneity in terms of canonical sEV tetraspanin molecules and cancer-associated protein biomarkers in both cancer cell line models and cancer patient samples. Our data explicitly demonstrate the selective enrichment of tetraspanins and cancer-associated protein biomarkers, in particular sEV subpopulations. Therefore, it is believed that the ESCP could enable the evaluation and broader application of sEV subpopulations as potential diagnostic disease biomarkers.

Discharge preparation: do healthcare professionals differ in their opinions?

Discharge preparation is a multiprofessional activity that is not always conducted efficiently. Perspectives of staff provide an insight into challenges and solutions for this organizational process. The study aimed to examine current discharge practice in one hospital and to compare perceptions of this activity between healthcare workers from different professions. A questionnaire was sent to 1344 staff in an English hospital. It consisted of items related to discharge, which were rated on a Likert scale, and included space for free text. Data were analyzed using descriptive and inferential statistics. The survey method has a number of limitations and conclusions must be considered with caution. A total of 455 usable questionnaires were returned from nurses/midwives, doctors and therapists/allied health professionals. Although respondents showed agreement on a number of areas, differences did arise, which could be linked, in part, to values and roles associated with specific healthcare disciplines. Tensions between professional groups were evident, especially between social workers, nurses and medics. Differences of opinion also appeared between practitioners, patients and carers. Different views among practitioners of discharge preparation could impede efficient joint working. Better understanding of the roles and expertise of team members might improve this process. Factors affecting discharge preparation need to be understood to reduce staff and consumer dissatisfaction and to avoid potential readmissions.

Upright Radiation Therapy-A Historical Reflection and Opportunities for Future Applications.

Since the early days of megavoltage Radiation Therapy (RT), the potential of delivering treatment to a sub group of patients in an upright position has been recognized. Compared to lying horizontally, treating patients in an upright position offers potential benefits in terms of patient comfort especially for patients experiencing dyspnoea and saliva accumulation when lying down. Dosimetric benefits can also be gained from changes in the volume and location of lungs and heart in an upright position, which are potentially advantageous for clinical situations including Hodgkin's disease, lung and breast malignancies. Since the 1950's, upright stabilization mechanisms have ranged from standalone chair based apparatus to couch-top attachments with increasingly customizable solutions. The introduction of Computed-Tomography (CT) based three-dimensional (3D) dosimetry in the 1980's-90's necessitated image acquisition in a horizontal position (supine or prone), significantly reducing options for alternative patient positioning and upright techniques. Despite this, upright techniques have still been utilized where clinically indicated for palliative and novel approaches often involving non-standard treatment scenarios. More recently, a small number of centers have reported on specialized equipment capable of acquiring planning data with the patient in a vertical position. The possibility of acquiring planning quality Cone Beam CT (CBCT) on linear accelerators has recently reinvigorated the potential to deliver highly accurate and targeted treatments to patients in an upright position. This paper reflects on the historical applications of upright RT and explores new possibilities for this technology in modern RT departments.

Robust, independent and relevant prognostic 18F-fluorodeoxyglucose positron emission tomography radiomics features in non-small cell lung cancer: Are there any?

In locally advanced lung cancer, established baseline clinical variables show limited prognostic accuracy and 18F-fluorodeoxyglucose positron emission tomography (FDG PET) radiomics features may increase accuracy for optimal treatment selection. Their robustness and added value relative to current clinical factors are unknown. Hence, we identify robust and independent PET radiomics features that may have complementary value in predicting survival endpoints. A 4D PET dataset (n = 70) was used for assessing the repeatability (Bland-Altman analysis) and independence of PET radiomics features (Spearman rank: |ρ|<0.5). Two 3D PET datasets combined (n = 252) were used for training and validation of an elastic net regularized generalized logistic regression model (GLM) based on a selection of clinical and robust independent PET radiomics features (GLMall). The fitted model performance was externally validated (n = 40). The performance of GLMall (measured with area under the receiver operating characteristic curve, AUC) was highest in predicting 2-year overall survival (0.66±0.07). No significant improvement was observed for GLMall compared to a model containing only PET radiomics features or only clinical variables for any clinical endpoint. External validation of GLMall led to AUC values no higher than 0.55 for any clinical endpoint. In this study, robust independent FDG PET radiomics features did not have complementary value in predicting survival endpoints in lung cancer patients. Improving risk stratification and clinical decision making based on clinical variables and PET radiomics features has still been proven difficult in locally advanced lung cancer patients.

Systems and people under pressure: the discharge process in an acute hospital.

AIMS: To understand the perspective of hospital-based health professionals with regard to preparing patients for discharge from an acute hospital in England. BACKGROUND: The hospital experience in England over recent years is characterised by increasing admission rates and decreasing length of stay. Legislation and policy initiatives have also focussed upon the need to reduce delayed discharges. Discharge preparation is known to be a complex intervention with multiple obstacles within and outside of the hospital setting. DESIGN: Qualitative. METHODS: Posters were displayed within a hospital asking health professionals to take part in a focus group. Maximum variation, in terms of job titles, was sought for within the sample. Focus groups were held in December 2006. Six senior members of staff divided into pairs to run them. All groups were taped and transcribed verbatim and analysed using a framework approach. RESULTS: Three focus groups were conducted, which involved 11 nurses, 15 allied health professionals, five social workers and one doctor. Analysis identified the following themes and sub themes: 1 Conflicting pressures on staff: Keeping patients in hospital vs. getting them out; Striving for flexibility within a system; A paucity of intermediary provision. 2 Casualties arising from conflicting pressures: Professionals losing their sense of professionalism; Patients being 'systematised'. CONCLUSIONS: Pressures described during focus groups stemmed from five main sources: external targets placed upon the system, internal hospital inflexibility and poor communication, the dominance of the medical model of care, a desire to address the complex needs of individuals and a lack of community services. Staff felt themselves to be victims of these competing pressures and that many of the solutions were beyond their influence. Staff described the dehumanising effect of sometimes having to ignore patient concerns, wishes and choices. RELEVANCE TO CLINICAL PRACTICE: Understanding of the pressures surrounding discharge could inform relevant service improvements.

What 18F-FDG PET Response-Assessment Method Best Predicts Survival After Curative-Intent Chemoradiation in Non-Small Cell Lung Cancer: EORTC, PERCIST, Peter Mac Criteria, or Deauville Criteria?

The optimal methodology for defining response with 18F-FDG PET after curative-intent chemoradiation for non-small cell lung cancer (NSCLC) is unknown. We compared survival outcomes according to the criteria of the European Organization for Research and Treatment of Cancer (EORTC), PERCIST 1.0, the Peter Mac metabolic visual criteria, and the Deauville criteria, respectively. Methods: Three prospective trials of chemoradiation for NSCLC, involving baseline and posttreatment 18F-FDG PET/CT imaging, were conducted between 2004 and 2016. Responses were categorized as complete metabolic response (CMR), partial metabolic response, stable metabolic disease, or progressive metabolic disease. Cox proportional-hazards models and log-rank tests assessed the impact of each response on overall survival (OS). Results: Eighty-seven patients underwent 18F-FDG PET/CT before and after radical chemoradiation for NSCLC. Follow-up 18F-FDG PET/CT scans were performed at a median of 89 d (interquartile range, 79-93 d) after radiotherapy. Median follow-up and OS after PET response imaging were 49 and 28 mo, respectively. Interobserver agreements for EORTC, PERCIST, Peter Mac, and Deauville had κ values of 0.76, 0.76, 0.87, and 0.84, respectively. All 4 response criteria were significantly associated with OS. Peter Mac and Deauville showed better fit than EORTC and PERCIST and distinguished better between CMR and non-CMR. Conclusion: All 4 response criteria were highly predictive of OS, but visual criteria showed greater interobserver agreement and stronger discrimination between CMR and non-CMR, highlighting the importance of visual assessment to recognize radiation pneumonitis, changes in lung configuration, and patterns of response.