133 research outputs found
Developing A Personal Decision Support Tool for Hospital Capacity Assessment and Querying
This article showcases a personal decision support tool (PDST) called
HOPLITE, for performing insightful and actionable quantitative assessments of
hospital capacity, to support hospital planners and health care managers. The
tool is user-friendly and intuitive, automates tasks, provides instant
reporting, and is extensible. It has been developed as an Excel Visual Basic
for Applications (VBA) due to its perceived ease of deployment, ease of use,
Office's vast installed userbase, and extensive legacy in business. The
methodology developed in this article bridges the gap between mathematical
theory and practice, which our inference suggests, has restricted the uptake
and or development of advanced hospital planning tools and software. To the
best of our knowledge, no personal decision support tool (PDST) has yet been
created and installed within any existing hospital IT systems, to perform the
aforementioned tasks. This article demonstrates that the development of a PDST
for hospitals is viable and that optimization methods can be embedded quite
simply at no cost. The results of extensive development and testing indicate
that HOPLITE can automate many nuanced tasks. Furthermore, there are few
limitations and only minor scalability issues with the application of free to
use optimization software. The functionality that HOPLITE provides may make it
easier to calibrate hospitals strategically and/or tactically to demands. It
may give hospitals more control over their case-mix and their resources,
helping them to operate more proactively and more efficiently.Comment: 33 pages, 11 tables, 17 figure
Analytical Techniques to Support Hospital Case Mix Planning
This article introduces analytical techniques and a decision support tool to
support capacity assessment and case mix planning (CMP) approaches previously
created for hospitals. First, an optimization model is proposed to analyse the
impact of making a change to an existing case mix. This model identifies how
other patient types should be altered proportionately to the changing levels of
hospital resource availability. Then we propose multi-objective decision-making
techniques to compare and critique competing case mix solutions obtained. The
proposed techniques are embedded seamlessly within an Excel Visual Basic for
Applications (VBA) personal decision support tool (PDST), for performing
informative quantitative assessments of hospital capacity. The PDST reports
informative metrics of difference and reports the impact of case mix
modifications on the other types of patient present. The techniques developed
in this article provide a bridge between theory and practice that is currently
missing and provides further situational awareness around hospital capacity.Comment: 20 pages, 11 tables, 6 figure
Multicriteria Optimization Techniques for Understanding the Case Mix Landscape of a Hospital
Various medical and surgical units operate in a typical hospital and to treat
their patients these units compete for infrastructure like operating rooms (OR)
and ward beds. How that competition is regulated affects the capacity and
output of a hospital. This article considers the impact of treating different
patient case mix (PCM) in a hospital. As each case mix has an economic
consequence and a unique profile of hospital resource usage, this consideration
is important. To better understand the case mix landscape and to identify those
which are optimal from a capacity utilisation perspective, an improved
multicriteria optimization (MCO) approach is proposed. As there are many
patient types in a typical hospital, the task of generating an archive of
non-dominated (i.e., Pareto optimal) case mix is computationally challenging.
To generate a better archive, an improved parallelised epsilon constraint
method (ECM) is introduced. Our parallel random corrective approach is
significantly faster than prior methods and is not restricted to evaluating
points on a structured uniform mesh. As such we can generate more solutions.
The application of KD-Trees is another new contribution. We use them to perform
proximity testing and to store the high dimensional Pareto frontier (PF). For
generating, viewing, navigating, and querying an archive, the development of a
suitable decision support tool (DST) is proposed and demonstrated.Comment: 38 pages, 17 figures, 11 table
The Efficacy of Utility Functions for Multicriteria Hospital Case-Mix Planning
A new approach to perform hospital case-mix planning (CMP) is introduced in
this article. Our multi-criteria approach utilises utility functions (UF) to
articulate the preferences and standpoint of independent decision makers
regarding outputs. The primary aim of this article is to test whether a utility
functions method (UFM) based upon the scalarization of aforesaid UF is an
appropriate quantitative technique to, i) distribute hospital resources to
different operating units, and ii) provide a better capacity allocation and
case mix. Our approach is motivated by the need to provide a method able to
evaluate the trade-off between different stakeholders and objectives of
hospitals. To the best of our knowledge, no such approach has been considered
before in the literature. As we will later show, this idea addresses various
technical limitations, weaknesses, and flaws in current CMP. The efficacy of
the aforesaid approach is tested on a case study of a large tertiary hospital.
Currently UF are not used by hospital managers, and real functions are
unavailable, hence, 14 rational options are tested. Our exploratory analysis
has provided important guidelines for the application of these UF. It indicates
that these UF provide a valuable starting point for planners, managers, and
executives of hospitals to impose their goals and aspirations. In conclusion,
our approach may be better at identifying case mix that users want to treat and
seems more capable of modelling the varying importance of different levels of
output. Apart from finding desirable case mixes to consider, the approach can
provide important insights via a sensitivity analysis of the parameters of each
UF.Comment: 35 pages, 6 tables, 29 figure
Strongly exchange-coupled triplet pairs in an organic semiconductor
From biological complexes to devices based on organic semiconductors, spin interactions play a key role in the function of molecular systems. For instance, triplet-pair reactions impact operation of organic light-emitting diodes as well as photovoltaic devices. Conventional models for triplet pairs assume they interact only weakly. Here, using electron spin resonance, we observe long-lived, strongly-interacting triplet pairs in an organic semiconductor, generated via singlet fission. Using coherent spin-manipulation of these two-triplet states, we identify exchange-coupled (spin-2) quintet complexes co-existing with weakly coupled (spin-1) triplets. We measure strongly coupled pairs with a lifetime approaching 3 µs and a spin coherence time approaching 1 µs, at 10 K. Our results pave the way for the utilization of high-spin systems in organic semiconductors.Gates-Cambridge Trust, Winton Programme for the Physics of Sustainability, Freie Universität Berlin within the Excellence Initiative of the German Research Foundation, Engineering and Physical Sciences Research Council (Grant ID: EP/G060738/1)This is the author accepted manuscript. The final version is available from Nature Publishing Group at http://dx.doi.org/10.1038/nphys3908
Somatic sequence alterations in twenty-one genes selected by expression profile analysis of breast carcinomas
Abstract Introduction Genomic alterations have been observed in breast carcinomas that affect the capacity of cells to regulate proliferation, signaling, and metastasis. Re-sequence studies have investigated candidate genes based on prior genetic observations (changes in copy number or regions of genetic instability) or other laboratory observations and have defined critical somatic mutations in genes such as TP53 and PIK3CA. Methods We have extended the paradigm and analyzed 21 genes primarily identified by expression profiling studies, which are useful for breast cancer subtyping and prognosis. This study conducted a bidirectional re-sequence analysis of all exons and 5', 3', and evolutionarily conserved regions (spanning more than 16 megabases) in 91 breast tumor samples. Results Eighty-seven unique somatic alterations were identified in 16 genes. Seventy-eight were single base pair alterations, of which 23 were missense mutations; 55 were distributed across conserved intronic regions or the 5' and 3' regions. There were nine insertion/deletions. Because there is no a priori way to predict whether any one of the identified synonymous and noncoding somatic alterations disrupt function, analysis unique to each gene will be required to establish whether it is a tumor suppressor gene or whether there is no effect. In five genes, no somatic alterations were observed. Conclusion The study confirms the value of re-sequence analysis in cancer gene discovery and underscores the importance of characterizing somatic alterations across genes that are related not only by function, or functional pathways, but also based upon expression patterns
Which patients with metastatic hormone-sensitive prostate cancer benefit from docetaxel: a systematic review and meta-analysis of individual participant data from randomised trials
BACKGROUND: Adding docetaxel to androgen deprivation therapy (ADT) improves survival in patients with metastatic, hormone-sensitive prostate cancer, but uncertainty remains about who benefits most. We therefore aimed to obtain up-to-date estimates of the overall effects of docetaxel and to assess whether these effects varied according to prespecified characteristics of the patients or their tumours. METHODS: The STOPCAP M1 collaboration conducted a systematic review and meta-analysis of individual participant data. We searched MEDLINE (from database inception to March 31, 2022), Embase (from database inception to March 31, 2022), the Cochrane Central Register of Controlled Trials (from database inception to March 31, 2022), proceedings of relevant conferences (from Jan 1, 1990, to Dec 31, 2022), and ClinicalTrials.gov (from database inception to March 28, 2023) to identify eligible randomised trials that assessed docetaxel plus ADT compared with ADT alone in patients with metastatic, hormone-sensitive prostate cancer. Detailed and updated individual participant data were requested directly from study investigators or through relevant repositories. The primary outcome was overall survival. Secondary outcomes were progression-free survival and failure-free survival. Overall pooled effects were estimated using an adjusted, intention-to-treat, two-stage, fixed-effect meta-analysis, with one-stage and random-effects sensitivity analyses. Missing covariate values were imputed. Differences in effect by participant characteristics were estimated using adjusted two-stage, fixed-effect meta-analysis of within-trial interactions on the basis of progression-free survival to maximise power. Identified effect modifiers were also assessed on the basis of overall survival. To explore multiple subgroup interactions and derive subgroup-specific absolute treatment effects we used one-stage flexible parametric modelling and regression standardisation. We assessed the risk of bias using the Cochrane Risk of Bias 2 tool. This study is registered with PROSPERO, CRD42019140591. FINDINGS: We obtained individual participant data from 2261 patients (98% of those randomised) from three eligible trials (GETUG-AFU15, CHAARTED, and STAMPEDE trials), with a median follow-up of 72 months (IQR 55-85). Individual participant data were not obtained from two additional small trials. Based on all included trials and patients, there were clear benefits of docetaxel on overall survival (hazard ratio [HR] 0·79, 95% CI 0·70 to 0·88; p<0·0001), progression-free survival (0·70, 0·63 to 0·77; p<0·0001), and failure-free survival (0·64, 0·58 to 0·71; p<0·0001), representing 5-year absolute improvements of around 9-11%. The overall risk of bias was assessed to be low, and there was no strong evidence of differences in effect between trials for all three main outcomes. The relative effect of docetaxel on progression-free survival appeared to be greater with increasing clinical T stage (pinteraction=0·0019), higher volume of metastases (pinteraction=0·020), and, to a lesser extent, synchronous diagnosis of metastatic disease (pinteraction=0·077). Taking into account the other interactions, the effect of docetaxel was independently modified by volume and clinical T stage, but not timing. There was no strong evidence that docetaxel improved absolute effects at 5 years for patients with low-volume, metachronous disease (-1%, 95% CI -15 to 12, for progression-free survival; 0%, -10 to 12, for overall survival). The largest absolute improvement at 5 years was observed for those with high-volume, clinical T stage 4 disease (27%, 95% CI 17 to 37, for progression-free survival; 35%, 24 to 47, for overall survival). INTERPRETATION: The addition of docetaxel to hormone therapy is best suited to patients with poorer prognosis for metastatic, hormone-sensitive prostate cancer based on a high volume of disease and potentially the bulkiness of the primary tumour. There is no evidence of meaningful benefit for patients with metachronous, low-volume disease who should therefore be managed differently. These results will better characterise patients most and, importantly, least likely to gain benefit from docetaxel, potentially changing international practice, guiding clinical decision making, better informing treatment policy, and improving patient outcomes. FUNDING: UK Medical Research Council and Prostate Cancer UK
A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.
We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis
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