68 research outputs found
Comparing health workforce forecasting approaches for healthcare planning: The case for ophthalmologists
Health workforce planning is essential in the provision of quality healthcare. Several approaches to planning are customarily used
and advocated, each with unique underlying assumptions. Thus, a thorough understanding of each assumption is required in
order to make an informed decision on the choice of forecasting approach to be used. For illustration, we compare results for
eye care requirements in Singapore using three established workforce forecasting approaches â workforce-to-population-ratio,
needs based approach, utilization based approach â and a proposed robust integrated approach to discuss the appropriateness of
each approach under various scenarios. Four simulation models using the systems modeling methodology of system dynamics
were developed for use in each approach. These models were initialized and simulated using the example of eye care workforce
planning in Singapore, to project the number of ophthalmologists required up to the year 2040 under the four different approaches.
We found that each approach projects a different number of ophthalmologists required over time. The needs based approach tends
to project the largest number of required ophthalmologists, followed by integrated, utilization based and workforce-to-population
ratio approaches in descending order. The four different approaches vary widely in their forecasted workforce requirements and
reinforce the need to be discerning of the fundamental differences of each approach in order to choose the most appropriate
one. Further, health workforce planning should also be approached in a comprehensive and integrated manner that accounts for
developments in demographic and healthcare systems
Future requirements for and supply of ophthalmologists for an aging population in Singapore
#### Background
Singaporeâs population, as that of many other countries, is aging; this is likely to lead to an increase in eye diseases and the demand for eye care. Since ophthalmologist training is long and expensive, early planning is essential. This paper forecasts workforce and training requirements for Singapore up to the year 2040 under several plausible future scenarios.
#### Methods
The Singapore Eye Care Workforce Model was created as a continuous time compartment model with explicit workforce stocks using system dynamics. The model has three modules: prevalence of eye disease, demand, and workforce requirements. The model is used to simulate the prevalence of eye diseases, patient visits, and workforce requirements for the public sector under different scenarios in order to determine training requirements.
#### Results
Four scenarios were constructed. Under the baseline business-as-usual scenario, the required number of ophthalmologists is projected to increase by 117% from 2015 to 2040.
Under the current policy scenario (assuming an increase of service uptake due to increased awareness, availability, and accessibility of eye care services), the increase will be 175%, while under the new model of care scenario (considering the additional effect of providing some services by non-ophthalmologists) the increase will only be 150%. The moderated workload scenario (assuming in addition a reduction of the clinical workload) projects an increase in the required number of ophthalmologists of 192% by 2040.
Considering the uncertainties in the projected demand for eye care services, under the business-as-usual scenario, a residency intake of 8â22 residents per year is required, 17â21 under the current policy scenario, 14â18 under the new model of care scenario, and, under the moderated workload scenario, an intake of 18â23 residents per year is required.
#### Conclusions
The results show that under all scenarios considered, Singaporeâs aging and growing population will result in an almost doubling of the number of Singaporeans with eye conditions, a significant increase in public sector eye care demand and, consequently, a greater requirement for ophthalmologists
Ovarian cancer risk factors by tumor aggressiveness : An analysis from the Ovarian Cancer Cohort Consortium
Ovarian cancer risk factors differ by histotype; however, within subtype, there is substantial variability in outcomes. We hypothesized that risk factor profiles may influence tumor aggressiveness, defined by time between diagnosis and death, independent of histology. Among 1.3 million women from 21 prospective cohorts, 4,584 invasive epithelial ovarian cancers were identified and classified as highly aggressive (death in = 35 vs. 20 to <25 kg/m(2), 1.93 [1.46-2.56] and current smoking (vs. never, 1.30 [1.07-1.57]) were associated with increased risk of highly aggressive disease. Results were similar within histotypes. Ovarian cancer risk factors may be directly associated with subtypes defined by tumor aggressiveness, rather than through differential effects on histology. Studies to assess biological pathways are warranted.Peer reviewe
Proceedings of the International Cancer Imaging Society (ICIS) 16th Annual Teaching Course
Table of contents
O1 Tumour heterogeneity: what does it mean?
Dow-Mu Koh
O2 Skeletal sequelae in adult survivors of childhood cancer
Sue Creviston Kaste
O3 Locoregional effects of breast cancer treatment
Sarah J Vinnicombe
O4 Imaging of cancer therapy-induced CNS toxicity
Giovanni Morana, Andrea Rossi
O5 Screening for lung cancer
Christian J. Herold
O6Risk stratification of lung nodules
Theresa C. McLoud
O7 PET imaging of pulmonary nodules
Kirk A Frey
O8 Transarterial tumour therapy
Bernhard Gebauer
O9 Interventional radiology in paediatric oncology
Derek Roebuck
O10 Image guided prostate interventions
Jurgen J. FĂŒtterer
O11 Imaging cancer predisposition syndromes
Alexander J. Towbin
O12Chest and chest wall masses
Thierry AG Huisman
O13 Abdominal masses: good or bad?
Anne MJB Smets
O14 Hepatobiliary MR contrast: enhanced liver MRI for HCC diagnosis and management
Giovanni Morana
O15 Role of US elastography and multimodality fusion for managing patients with chronic liver disease and HCC
Jeong Min Lee
O16 Opportunities and challenges in imaging metastatic disease
Hersh Chandarana
O17 Diagnosis, treatment monitoring, and follow-up of lymphoma
Marius E. Mayerhoefer, Markus Raderer, Alexander Haug
O18 Managing high-risk and advanced prostate cancer
Matthias Eiber
O19 Immunotherapy: imaging challenges
Bernhard Gebauer
O20 RECIST and RECIST 1.1
Andrea Rockall
O21 Challenges of RECIST in oncology imaging basics for the trainee and novice
Aslam Sohaib
O22 Lymphoma: PET for interim and end of treatment response assessment: a usersâ guide to the Deauville Score
Victoria S Warbey
O23 Available resources
Hebert Alberto Vargas
O24 ICIS e-portal and the online learning community
Dow-Mu Koh
O25 Benign lesions that mimic pancreatic cancer
Jay P Heiken
O26 Staging and reporting pancreatic malignancies
Isaac R Francis, Mahmoud, M Al-Hawary, Ravi K Kaza
O27 Intraductal papillary mucinous neoplasm
Giovanni Morana
O28 Cystic pancreatic tumours
Mirko DâOnofrio
O29 Diffusion-weighted imaging of head and neck tumours
Harriet C. Thoeny
O30 Radiation injury in the head and neck
Ann D King
O31 PET/MR of paediatric brain tumours
Giovanni Morana, Arnoldo Piccardo, Maria Luisa GarrĂš, Andrea Rossi
O32 Structured reporting and beyond
Hebert Alberto Vargas
O33 Massachusetts General Hospital experience with structured reporting
Theresa C. McLoud
O34 The oncologistâs perspective: what the oncologist needs to know
Nick Reed
O35 Towards the cure of all children with cancer: global initiatives in pediatric oncology
Carlos Rodriguez-Galindo
O36 Multiparametric imaging of renal cancers
Hersh Chandarana
O37 Linking imaging features of renal disease and their impact on management strategies
Hebert Alberto Vargas
O38 Adrenals, retroperitoneum and peritoneum
Isaac R Francis, Ashish P Wasnik
O39 Lung and pleura
Stefan Diederich
O40 Advances in MRI
Jurgen J. FĂŒtterer
O41 Advances in molecular imaging
Wim J.G. Oyen
O42 Incorporating advanced imaging, impact on treatment selection and patient outcome
Cheng Lee Chaw, Nicholas van As
S1 Combining ADC-histogram features improves performance of MR diffusion-weighted imaging for Lymph node characterisation in cervical cancer
Igor Vieira, Frederik De Keyzer, Elleke Dresen, Sileny Han, Ignace Vergote, Philippe Moerman, Frederic Amant, Michel Koole, Vincent Vandecaveye
S2 Whole-body diffusion-weighted MRI for surgical planning in patients with colorectal cancer and peritoneal metastases
R Dresen, S De Vuysere, F De Keyzer, E Van Cutsem, A DâHoore, A Wolthuis, V Vandecaveye
S3 Role of apparent diffusion coefficient (ADC) diffusion-weighted MRI for predicting extra capsular extension of prostate cancer.
P. Pricolo ([email protected]), S. Alessi, P. Summers, E. Tagliabue, G. Petralia
S4 Generating evidence for clinical benefit of PET/CT â are management studies sufficient as surrogate for patient outcome?
C. Pfannenberg, B. GĂŒckel, SC SchĂŒle, AC MĂŒller, S. Kaufmann, N. Schwenzer, M. Reimold,C. la Fougere, K. Nikolaou, P. Martus
S5 Heterogeneity of treatment response in skeletal metastases from breast cancer with 18F-fluoride and 18F-FDG PET
GJ Cook, GK Azad, BP Taylor, M Siddique, J John, J Mansi, M Harries, V Goh
S6 Accuracy of suspicious breast imagingâcan we tell the patient?
S Seth, R Burgul, A Seth
S7 Measurement method of tumour volume changes during neoadjuvant chemotherapy affects ability to predict pathological response
S Waugh, N Muhammad Gowdh, C Purdie, A Evans, E Crowe, A Thompson, S Vinnicombe
S8 Diagnostic yield of CT IVU in haematuria screening
F. Arfeen, T. Campion, E. Goldstraw
S9 Percutaneous radiofrequency ablation of unresectable locally advanced pancreatic cancer: preliminary results
DâOnofrio M, Ciaravino V, Crosara S, De Robertis R, Pozzi Mucelli R
S10 Iodine maps from dual energy CT improve detection of metastases in staging examinations of melanoma patients
M. Uhrig, D. Simons, H. Schlemmer
S11Can contrast enhanced CT predict pelvic nodal status in malignant melanoma of the lower limb?
Kate Downey
S12 Current practice in the investigation for suspected Paraneoplastic Neurological Syndromes (PNS) and positive malignancy yield.
S Murdoch, AS Al-adhami, S Viswanathan
P1 Technical success and efficacy of Pulmonary Radiofrequency ablation: an analysis of 207 ablations
S Smith, P Jennings, D Bowers, R Soomal
P2 Lesion control and patient outcome: prospective analysis of radiofrequency abaltion in pulmonary colorectal cancer metastatic disease
S Smith, P Jennings, D Bowers, R Soomal
P3 Hepatocellular carcinoma in a post-TB patient: case of tropical infections and oncologic imaging challenges
TM Mutala, AO Odhiambo, N Harish
P4 Role of apparent diffusion coefficient (ADC) diffusion-weighted MRI for predicting extracapsular extension of prostate cancer
P. Pricolo, S. Alessi, P. Summers, E. Tagliabue, G. Petralia
P5 What a difference a decade makes; comparison of lung biopsies in Glasgow 2005 and 2015
M. Hall, M. Sproule, S. Sheridan
P6 Solid pseudopapillary tumour of pancreas: imaging features of a rare neoplasm
KY Thein, CH Tan, YL Thian, CM Ho
P7 MDCT - pathological correlation in colon adenocarcinoma staging: preliminary experience
S De Luca, C Carrera, V Blanchet, L AlarcĂłn, E Eyheremnedy
P8 Image guided biopsy of thoracic masses and reduction of pneumothorax risk: 25Â years experience
B K Choudhury, K Bujarbarua, G Barman
P9 Tumour heterogeneity analysis of 18F-FDG-PET for characterisation of malignant peripheral nerve sheath tumours in neurofibromatosis-1
GJ Cook, E Lovat, M Siddique, V Goh, R Ferner, VS Warbey
P10 Impact of introduction of vacuum assisted excision (VAE) on screen detected high risk breast lesions
L Potti, B Kaye, A Beattie, K Dutton
P11 Can we reduce prevalent recall rate in breast screening?
AA Seth, F Constantinidis, H Dobson
P12 How to reduce prevalent recall rate? Identifying mammographic lesions with low Positive Predictive Value (PPV)
AA Seth ([email protected]), F Constantinidis, H Dobson
P13 Behaviour of untreated pulmonary thrombus in oncology patients diagnosed with incidental pulmonary embolism on CT
R. Bradley, G. Bozas, G. Avery, A. Stephens, A. Maraveyas
P14 A one-stop lymphoma biopsy service â is it possible?
S Bhuva, CA Johnson, M Subesinghe, N Taylor
P15 Changes in the new TNM classification for lung cancer (8th edition, effective January 2017)
LE Quint, RM Reddy, GP Kalemkerian
P16 Cancer immunotherapy: a review of adequate imaging assessment
G GonzĂĄlez Zapico, E Gainza Jauregui, R Ălvarez Francisco, S Ibåñez Alonso, I Tavera Bahillo, L MĂșgica Ălvarez
P17 Succinate dehydrogenase mutations and their associated tumours
O Francies, R Wheeler, L Childs, A Adams, A Sahdev
P18 Initial experience in the usefulness of dual energy technique in the abdomen
SE De Luca, ME Casalini Vañek, MD Pascuzzi, T Gillanders, PM Ramos, EP Eyheremendy
P19 Recognising the serious complication of Richterâs transformation in CLL patients
C Stove, M Digby
P20 Body diffusion-weighted MRI in oncologic practice: truths, tricks and tips
M. Nazar, M. Wirtz, MD. Pascuzzi, F. Troncoso, F. Saguier, EP. Eyheremendy
P21 Methotrexate-induced leukoencephalopathy in paediatric ALL Patients
D.J. Quint, L. Dang, M. Carlson, S. Leber, F. Silverstein
P22 Pitfalls in oncology CT reporting. A pictorial review
R Rueben, S Viswanathan
P23 Imaging of perineural extension in head and neck tumours
B Nazir, TH Teo, JB Khoo
P24 MRI findings of molecular subtypes of breast cancer: a pictorial primer
K Sharma, N Gupta, B Mathew, T Jeyakumar, K Harkins
P25 When cancer canât wait! A pictorial review of oncological emergencies
K Sharma, B Mathew, N Gupta, T Jeyakumar, S Joshua
P26 MRI of pancreatic neuroendocrine tumours: an approach to interpretation
D Christodoulou, S Gourtsoyianni, A Jacques, N Griffin, V Goh
P27 Gynaecological cancers in pregnancy: a review of imaging
CA Johnson, J Lee
P28 Suspected paraneoplastic neurological syndromes - review of published recommendations to date, with proposed guideline/flowchart
JA Goodfellow, AS Al-adhami, S Viswanathan
P29 Multi-parametric MRI of the pelvis for suspected local recurrence of prostate cancer after radical prostatectomy
R Bradley
P30 Utilisation of PI-RADS version 2 in multi-parametric MRI of the prostate; 12-months experience
R Bradley
P31 Radiological assessment of the post-chemotherapy liver
A Yong, S Jenkins, G Joseph
P32 Skeletal staging with MRI in breast cancer â what the radiologist needs to know
S Bhuva, K Partington
P33 Perineural spread of lympoma: an educational review of an unusual distribution of disease
CA Johnson, S Bhuva, M Subesinghe, N Taylor
P34 Visually isoattenuating pancreatic adenocarcinoma. Diagnostic imaging tools.
C Carrera, A Zanfardini, S De Luca, L AlarcĂłn, V Blanchet, EP Eyheremendy
P35 Imaging of larynx cancer: when is CT, MRI or FDG PET/CT the best test?
K Cavanagh, E Lauhttp://deepblue.lib.umich.edu/bitstream/2027.42/134651/1/40644_2016_Article_79.pd
Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.
Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer
Combination of searches for heavy spin-1 resonances using 139 fbâ1 of proton-proton collision data at s = 13 TeV with the ATLAS detector
A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fbâ1 of proton-proton collisions at
= 13 TeV collected during 2015â2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb,
, and tb) or third-generation leptons (ÏÎœ and ÏÏ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion
Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic
This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic
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