93 research outputs found
An overview of the Upper Paleozoic-Mesozoic stratigraphy of the NE Atlantic region
This study describes the distribution and stratigraphic range of the Upper PaleozoicâMesozoic succession in the NE Atlantic region, and is correlated between conjugate-margins and along the axis of the NE Atlantic rift system. The stratigraphic framework has yielded important new constraints on the timing and nature of sedimentary basin development in the NE Atlantic, with implications for rifting and the breakup of the Pangaean supercontinent. From a regional perspective, the PermianâTriassic succession records a northward transition from an arid interior to a passively-subsiding, mixed carbonate/siliciclastic shelf margin. A Late Permianâearliest Triassic rift pulse has regional expression in the stratigraphic record. A fragmentary paralic to shallow-marine Lower Jurassic succession reflects Early Jurassic thermal subsidence and mild extensional tectonism; this was interrupted by widespread Mid-Jurassic uplift and erosion, and followed by an intense phase of Late Jurassic rifting in some (but not all) parts of the NE Atlantic region. The Cretaceous succession is dominated by thick basinal-marine deposits, which accumulated within and along a broad zone of extension and subsidence between Rockall and NE Greenland. There is no evidence for a substantive and continuous rift system along the proto-NE Atlantic until the Late Cretaceous
Sequential design of computer experiments for the estimation of a probability of failure
This paper deals with the problem of estimating the volume of the excursion
set of a function above a given threshold,
under a probability measure on that is assumed to be known. In
the industrial world, this corresponds to the problem of estimating a
probability of failure of a system. When only an expensive-to-simulate model of
the system is available, the budget for simulations is usually severely limited
and therefore classical Monte Carlo methods ought to be avoided. One of the
main contributions of this article is to derive SUR (stepwise uncertainty
reduction) strategies from a Bayesian-theoretic formulation of the problem of
estimating a probability of failure. These sequential strategies use a Gaussian
process model of and aim at performing evaluations of as efficiently as
possible to infer the value of the probability of failure. We compare these
strategies to other strategies also based on a Gaussian process model for
estimating a probability of failure.Comment: This is an author-generated postprint version. The published version
is available at http://www.springerlink.co
Factors associated with timeliness of post-primary care referral, diagnosis and treatment for lung cancer: population-based, data-linkage study
BACKGROUND: The NHS Cancer Plan for England set waiting time targets for cancer referral (14 days from GP referral to first hospital appointment) and treatment (31 days from diagnosis, 62 days from urgent GP referral). Interim diagnostic intervals can also be calculated. The factors that influence timely post-primary care referral, diagnosis and treatment for lung cancer are not known. METHODS: Northern and Yorkshire Cancer Registry, Hospital Episode Statistics and lung cancer audit data sets were linked. Logistic regression was used to investigate the factors (socioeconomic position, age, sex, histology, co-morbidity, year of diagnosis, stage and performance status (PS)) that may influence the likelihood of referral, diagnosis and treatment within target, for 28â733 lung cancer patients diagnosed in 2006â2010. RESULTS: Late-stage, poor PS and small-cell histology were associated with a higher likelihood of post-primary care referral, diagnosis and treatment within target. Older patients were significantly less likely to receive treatment within the 31-day (odds ratio (OR)=0.79, 95% confidence interval (CI) 0.69â0.91) and 62-day target (OR=0.80, 95% CI 0.67â0.95) compared with younger patients. CONCLUSIONS: Older patients waited longer for treatment and this may be unjustified. Patients who appeared ill were referred, diagnosed and treated more quickly and this âsicker quickerâ effect may cancel out system socioeconomic inequalities that might result in longer time intervals for more deprived patients
Time intervals from first symptom to treatment of cancer: a cohort study of 2,212 newly diagnosed cancer patients
<p>Abstract</p> <p>Background</p> <p>Delay in diagnosis of cancer may worsen prognosis. The aim of this study is to explore patient-, general practitioner (GP)- and system-related delay in the interval from first cancer symptom to diagnosis and treatment, and to analyse the extent to which delays differ by cancer type.</p> <p>Methods</p> <p>Population-based cohort study conducted in 2004-05 in the County of Aarhus, Denmark (640,000 inhabitants). Data were collected from administrative registries and questionnaires completed by GPs on 2,212 cancer patients newly diagnosed during a 1-year period. Median delay (in days) with interquartile interval (IQI) was the main outcome measure.</p> <p>Results</p> <p>Median total delay was 98 days (IQI 57-168). Most of the total delay stemmed from patient (median 21 days (7-56)) and system delay (median 55 days (32-93)). Median GP delay was 0 (0-2) days. Total delay was shortest among patients with ovarian (median 60 days (45-112)) and breast cancer (median 65 days (39-106)) and longest among patients with prostate (median 130 days (89-254)) and bladder cancer (median 134 days (93-181)).</p> <p>Conclusion</p> <p>System delay accounted for a substantial part of the total delay experienced by cancer patients. This points to a need for shortening clinical pathways if possible. A long patient delay calls for research into patient awareness of cancer. For all delay components, special focus should be given to the 4<sup>th </sup>quartile of patients with the longest time intervals and we need research into the quality of the diagnostic work-up process. We found large variations in delay for different types of cancer. Improvements should therefore target both the population at large and the specific needs associated with individual cancer types and their symptoms.</p
Case management used to optimize cancer care pathways: A systematic review
<p>Abstract</p> <p>Background</p> <p>Reports of inadequate cancer patient care have given rise to various interventions to support cancer care pathways which, overall, seem poorly studied. Case management (CM) is one method that may support a cost-effective, high-quality patient-centred treatment and care.</p> <p>The purpose of this article was to summarise intervention characteristics, outcomes of interest, results, and validity components of the published randomized controlled trials (RCTs) examining CM as a method for optimizing cancer care pathways.</p> <p>Methods</p> <p>PubMed, Embase, Web of Science, CINAHL and The Cochrane Central Register of Controlled Trials were systematically searched for RCTs published all years up to August 2008. Identified papers were included if they passed the following standards. Inclusion criteria: 1) The intervention should meet the criteria for CM which includes multidisciplinary collaboration, care co-ordination, and it should include in-person meetings between patient and the case manager aimed at supporting, informing and educating the patient. 2) The intervention should focus on cancer patient care. 3) The intervention should aim to improve subjective or objective quality outcomes, and effects should be reported in the paper.</p> <p>Exclusion criteria: Studies centred on cancer screening or palliative cancer care.</p> <p>Data extraction was conducted in order to obtain a descriptive overview of intervention characteristics, outcomes of interest and findings. Elements of CONSORT guidelines and checklists were used to assess aspects of study validity.</p> <p>Results</p> <p>The searches identified 654 unique papers, of which 25 were retrieved for scrutiny. Seven papers were finally included. Intervention characteristics, outcomes studied, findings and methodological aspects were all very diverse.</p> <p>Conclusion</p> <p>Due to the scarcity of papers included (seven), significant heterogeneity in target group, intervention setting, outcomes measured and methodologies applied, no conclusions can be drawn about the effect of CM on cancer patient care.</p> <p>It is a major challenge that CM shrouds in a "black box", which means that it is difficult to determine which aspect(s) of interventions contribute to overall effects. More trials on rigorously developed CM interventions (opening up the "black box") are needed as is the re-testing of interventions and outcomes studied in various settings.</p
Understanding missed opportunities for more timely diagnosis of cancer in symptomatic patients after presentation.
The diagnosis of cancer is a complex, multi-step process. In this paper, we highlight factors involved in missed opportunities to diagnose cancer more promptly in symptomatic patients and discuss responsible mechanisms and potential strategies to shorten intervals from presentation to diagnosis. Missed opportunities are instances in which post-hoc judgement indicates that alternative decisions or actions could have led to more timely diagnosis. They can occur in any of the three phases of the diagnostic process (initial diagnostic assessment; diagnostic test performance and interpretation; and diagnostic follow-up and coordination) and can involve patient, doctor/care team, and health-care system factors, often in combination. In this perspective article, we consider epidemiological 'signals' suggestive of missed opportunities and draw on evidence from retrospective case reviews of cancer patient cohorts to summarise factors that contribute to missed opportunities. Multi-disciplinary research targeting such factors is important to shorten diagnostic intervals post presentation. Insights from the fields of organisational and cognitive psychology, human factors science and informatics can be extremely valuable in this emerging research agenda. We provide a conceptual foundation for the development of future interventions to minimise the occurrence of missed opportunities in cancer diagnosis, enriching current approaches that chiefly focus on clinical decision support or on widening access to investigations.We acknowledge the helpful and incisive comments by Dr Rikke Sand Andersen (Aarhus University, Denmark) in conceptualising this piece and in drafts of the manuscript. The work is independent research supported by different funding schemes. GL was supported by a Post-Doctoral Fellowship by the National Institute for Health Research (PDF-2011-04-047) until the end of 2014 and by a Cancer Research UK Clinician Scientist Fellowship award (A18180) from 2015. HS is supported by the VA Health Services Research and Development Service (CRE 12-033; Presidential Early Career Award for Scientists and Engineers USA 14-274), the VA National Center for Patient Safety, the Agency for Health Care Research and Quality (R01HS022087) and in part by the Houston VA HSR&D Center for Innovations in Quality, Effectiveness and Safety (CIN 13â413). PV was supported by CaP, funded by The Danish Cancer Society and the Novo Nordisk Foundation.This is the final version of the article. It first appeared at http://dx.doi.org/10.1038/bjc.2015.4
Factors influencing the speed of cancer diagnosis in rural Western Australia: A General Practice perspective
Introduction. The speed of diagnosis impacts on prognosis and survival in all types of cancer. In most cases survival and prognosis are significantly worse in rural and remote Australian populations who have less access to diagnostic and therapeutic services than metropolitan communities in this country. Research suggests that in general delays in diagnosis were a factor of misdiagnosis, the confounding effect of existing conditions and delayed or misleading investigation of symptoms. The aim of this study is to further explore the factors that impact on the speed of diagnosis in rural Western Australia with direct reference to General Practitioners (GPs) working in this setting.
Methods. The methodology consisted of a structured discussion of specific cases. GPs based in two rural locations in Western Australia were asked to identify up to eight clinical cases for discussion. A diversity of cases was requested encompassing those with timely and delayed diagnosis of cancer. Focus groups were held with the practitioners to identify which factors under six headings delayed or facilitated the diagnosis in each case. A structured summary of the discussion was relayed to a wider group of GPs to seek additional views or comments on specific factors that impact on the speed of cancer diagnosis in rural and remote locations in Australia.
Results. A number of factors affecting the speed of diagnosis were identified: the demographic shift towards a frailer and older population, presenting with multiple and complex diseases, increases the challenge to identify early cancer symptoms; seasonal and demanding work patterns leading to procrastination in presenting for medical care; unhelpful scheduling of specialist appointments; and the varying impact of informal networks and social relationships.
Conclusion. Within the limitations of this study we have generated a number of hypotheses that require formal evaluation: (1) GPs working within informal professional and social networks are better informed about their patients' health needs and have an advantage in making early diagnosis; (2) Despite the other differences in the population characteristics decentralising services would improve the prospect for timely diagnosis; and (3) Careful coordination of specialist appointments would improve the speed of diagnosis for rural patients. Š 2007 Jiwa et al; licensee BioMed Central Ltd
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