Imperial College London

DrMatthewWilliams

Faculty of MedicineDepartment of Surgery & Cancer

Honorary Senior Research Fellow
 
 
 
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Contact

 

+44 (0)20 3311 0733matthew.williams Website CV

 
 
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Location

 

Charing Cross HospitalCharing Cross Campus

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Summary

 

Publications

Publication Type
Year
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52 results found

Dadhania S, Wang JW, Yu B, Saleem W, Blake C, Shahabi L, Williams Met al., 2019, EARLY EFFECTS OF SURGERY AND RADIOTHERAPY ON ACTIVITY LEVELS IN PATIENTS WITH BRAIN TUMOURS: PRELIMINARY DATA FROM THE BRAINWEAR TRIAL, Meeting of the British-Neuro-Oncology-Society (BNOS), Publisher: OXFORD UNIV PRESS INC, Pages: 12-12, ISSN: 1522-8517

Conference paper

Macnair A, Sharkey A, Le Calvez K, Walters R, Smith L, Nelson A, Staffurth J, Williams M, Bloomfield D, Maher Jet al., 2019, The Trigger Project: The Challenge of Introducing Electronic Patient-Reported Outcome Measures Into a Radiotherapy Service., Clin Oncol (R Coll Radiol)

Journal article

Brodbelt AR, Barclay ME, Greenberg D, Williams M, Jenkinson MD, Karabatsou Ket al., 2019, The outcome of patients with surgically treated meningioma in England: 1999-2013. A cancer registry data analysis., British Journal of Neurosurgery, Pages: 1-7, ISSN: 0268-8697

Purpose: Meningiomas are the commonest predominantly non-malignant brain tumour in adults. The use of surgery appears to be increasing, and outcomes are thought to be good, but whole nation data for England is scarce. The aim of this report is to examine the epidemiology of patients operated for cranial and spinal meningioma in England, and to assess associations between outcomes and gender, age, meningioma site (cranial or spinal), and grade. Material and methods: A search strategy encompassing all patients coded with cranial and spinal meningioma treated between January 1999 and December 2013 was obtained from data linkage between the National Cancer Registration and Analysis Service and Hospital Episode Statistics for England. Results: 25,694 patients were diagnosed with meningioma in England between 1999 and 2013, in whom 24,302 were cranial and 1392 spinal. Of these patients, 14,229 (60%) cranial and 1188 (85%) spinal meningioma received surgery. Of those operated on 70.1% were women, and, where the tumour grade was recorded, 79.5% were WHO grade I, 18.4% grade II, and 2.1% grade III. Five and ten year net survival rates for surgically treated cranial meningiomas were respectively 90% and 81% for those with WHO grade I, 80% and 63% for grade II, and 30% and 15% for WHO grade III tumours. Overall survival after surgery is better in women, younger adults, and people with spinal or lower grade meningiomas. Outcomes have improved over the time period examined. Conclusion: The outcome for patients with meningioma is good and is improving. However, there remains a significant mortality related to the disease process.

Journal article

Laaniste L, Srivastava P, Stylianou T, Syed N, Cases-Cunillera S, Shkura K, Zeng Q, Rackham O, Langley S, Delahaye-Duriez A, O'Neill K, Williams M, Becker A, Roncaroli F, Petretto E, Johnson Met al., 2019, Integrated systems-genetic analyses reveal a network target for delaying glioma progression, Annals of Clinical and Translational Neurology, Vol: 6, Pages: 1616-1638, ISSN: 2328-9503

ObjectiveTo identify a convergent, multitarget proliferation characteristic for astrocytoma transformation that could be targeted for therapy discovery.MethodsUsing an integrated functional genomics approach, we prioritized networks associated with astrocytoma progression using the following criteria: differential co‐expression between grade II and grade III IDH1‐mutated and 1p/19q euploid astrocytomas, preferential enrichment for genetic risk to cancer, association with patient survival and sample‐level genomic features. Drugs targeting the identified multitarget network characteristic for astrocytoma transformation were computationally predicted using drug transcriptional perturbation data and validated using primary human astrocytoma cells.ResultsA single network, M2, consisting of 177 genes, was associated with glioma progression on the basis of the above criteria. Functionally, M2 encoded physically interacting proteins regulating cell cycle processes and analysis of genome‐wide gene‐regulatory interactions using mutual information and DNA–protein interactions revealed the known regulators of cell cycle processes FoxM1, B‐Myb, and E2F2 as key regulators of M2. These results suggest functional disruption of M2 via gene mutation or altered expression as a convergent pathway regulating astrocytoma transformation. By considering M2 as a multitarget drug target regulating astrocytoma transformation, we identified several drugs that are predicted to restore M2 expression in anaplastic astrocytoma toward its low‐grade profile and of these, we validated the known antiproliferative drug resveratrol as down‐regulating multiple nodes of M2 including at nanomolar concentrations achievable in human cerebrospinal fluid by oral dosing.InterpretationOur results identify M2 as a multitarget network characteristic for astrocytoma progression and encourage M2‐based drug screening to identify new compounds for preventing glioma transformation.

Journal article

Booth TC, Williams M, Luis A, Cardosa J, Keyoumars A, Shuaib Het al., 2019, Machine learning and glioma imaging biomarkers, Clinical Radiology, ISSN: 0009-9260

AIM: To review how machine learning (ML) is applied to imaging biomarkers in neuro-oncology, in particular for diagnosis, prognosis, and treatment response monitoring. MATERIALS AND METHODS: The PubMed and MEDLINE databases were searched for articles published before September 2018 using relevant search terms. The search strategy focused on articles applying ML to high-grade glioma biomarkers for treatment response monitoring, prognosis, and prediction. RESULTS: Magnetic resonance imaging (MRI) is typically used throughout the patient pathway because routine structural imaging provides detailed anatomical and pathological information and advanced techniques provide additional physiological detail. Using carefully chosen image features, ML is frequently used to allow accurate classification in a variety of scenarios. Rather than being chosen by human selection, ML also enables image features to be identified by an algorithm. Much research is applied to determining molecular profiles, histological tumour grade, and prognosis using MRI images acquired at the time that patients first present with a brain tumour. Differentiating a treatment response from a post-treatment-related effect using imaging is clinically important and also an area of active study (described here in one of two Special Issue publications dedicated to the application of ML in glioma imaging). CONCLUSION: Although pioneering, most of the evidence is of a low level, having been obtained retrospectively and in single centres. Studies applying ML to build neuro-oncology monitoring biomarker models have yet to show an overall advantage over those using traditional statistical methods. Development and validation of ML models applied to neuro-oncology require large, well-annotated datasets, and therefore multidisciplinary and multi-centre collaborations are necessary.

Journal article

Kroupa P, Morton C, Le Calvez K, Williams Met al., 2019, Assessing K-nearest neighbours algorithm for simple, interpretable time-to-event survival predictions over a range of simulated datasets, Pages: 367-372, ISSN: 1063-7125

© 2019 IEEE. Survival prediction is a key task in medicine. Existing models are based on statistical techniques, such as the Cox models and there is limited work on the application of machine learning. In this paper we demonstrate that the K-Nearest Neighbour algorithm can be used for survival prediction. We show that its performance is as good as that of standard techniques, and that it provides a clear interpretation of the results. We show that pre-processing methods improve performance, and evaluate the performance across 20 different datasets with differing properties to show that the model performs well under various conditions. For low event rate datasets we show that KNN can outperform the Cox model.

Conference paper

Hall PE, Lewis R, Syed N, Shaffer R, Evanson J, Ellis S, Williams M, Feng X, Johnston A, Thomson JA, Harris FP, Jena R, Matys T, Jefferies S, Smith K, Wu B-W, Bomalaski JS, Crook T, O'Neill K, Paraskevopoulos D, Khadeir RS, Sheaff M, Pacey S, Plowman PN, Szlosarek PWet al., 2019, A Phase I Study of Pegylated Arginine Deiminase ( Pegargiminase), Cisplatin, and Pemetrexed in Argininosuccinate Synthetase 1-Deficient Recurrent High-grade Glioma, CLINICAL CANCER RESEARCH, Vol: 25, Pages: 2708-2716, ISSN: 1078-0432

Journal article

Morton CE, Smith SF, Lwin T, George M, Williams Met al., 2019, What are the benefits of teaching medical students computer coding?, JMIR Medical Education, Vol: 5, ISSN: 2369-3762

Background:The ability to construct simple computer programs ("coding") is being progressively recognised as a life skill. Coding is now being taught to primary-school children world-wide, but current medical students usually lack coding skills, and current measures of computer literacy for medical students focus on the use of software and internet safety. There is a need to train a cohort of doctors who can both practice medicine and also engage in the development of useful, innovative technologies to increase efficiency and adapt to the modern medical world.Objective:The aim of the study was to address the following questions: 1) Is it possible to teach undergraduate medical students the basics of computer coding in a weekend? 2) How do students perceive the value of learning computer coding at medical school? 3) Do students see computer coding as an important skill for future doctors?Methods:We developed a 2-day coding course to teach self-selected cohorts of medical students basic coding. The course included a practical introduction to writing software, discussion of computational thinking, and how to discuss projects with mainstream computer scientists. We explored in focus groups whether students thought that coding has a place in the undergraduate medical curriculum.Results:Our results demonstrate that medical students who were complete novices at coding could be taught enough to be able to create simple usable clinical programs with 2 days of intensive teaching. In addition, 6 major themes emerged from the focus group 1) Making sense of coding 2) Developing the students’ skillset 3) The value of coding in medicine, research and business 4) Role of teaching coding in medical school 5) The concept of an enjoyable challenge 6) Comments on the course designConclusions:Medical students can acquire usable coding skills in a weekend course. They valued the teaching and identified that, as well as gaining coding skills, they had acquired an understan

Journal article

Hart MG, Hunter A, Hawkins N, Si S, Toni Fet al., 2018, First-line treatments for people with single or multiple brain metastases, Cochrane Database of Systematic Reviews, Vol: 2018

© 2018 The Cochrane Collaboration. This is a protocol for a Cochrane Review (Intervention). The objectives are as follows: To compare the safety and efficacy of surgery, radiotherapy, and chemotherapy as first-line treatment for people with single or multiple brain metastases, either alone or in combination.

Journal article

Brown NF, Williams M, Arkenau H-T, Fleming RA, Tolson J, Yan L, Zhang J, Swartz L, Singh R, Auger KR, Lenox L, Cox D, Lewis Y, Plisson C, Searle G, Saleem A, Blagden S, Mulholland Pet al., 2018, A study of the focal adhesion kinase inhibitor GSK2256098 in patients with recurrent glioblastoma with evaluation of tumor penetration of [C-11]GSK2256098, NEURO-ONCOLOGY, Vol: 20, Pages: 1634-1642, ISSN: 1522-8517

Journal article

Williams M, Rabinowicz S, Butz R, Hommerson Aet al., CSBN: A Hybrid Approach For Survival Time Prediction With Missing Data, AALTD: 3nd ECML/PKDD Workshop on Advanced Analytics and Learning on Temporal Data

Conference paper

Wong S-L, Ricketts K, Royle G, Williams M, Mendes Ret al., 2018, A methodology to extract outcomes from routine healthcare data for patients with locally advanced non-small cell lung cancer, BMC Health Services Research, Vol: 18, ISSN: 1472-6963

BACKGROUND: Outcomes for patients in UK with locally advanced non-small cell lung cancer (LA NSCLC) are amongst the worst in Europe. Assessing outcomes is important for analysing the effectiveness of current practice. However, data quality is inconsistent and regular large scale analysis is challenging. This project investigates the use of routine healthcare datasets to determine progression free survival (PFS) and overall survival (OS) of patients treated with primary radical radiotherapy for LA NSCLC. METHODS: All LA NSCLC patients treated with primary radical radiotherapy in a 2 year period were identified and paired manual and routine data generated for an initial pilot study. Manual data was extracted information from hospital records and considered the gold standard. Key time points were date of diagnosis, recurrence, death or last clinical encounter. Routine data was collected from various data sources including, Hospital Episode Statistics, Personal Demographic Service, chemotherapy data, and radiotherapy datasets. Relevant event dates were defined by proxy time points and refined using backdating and time interval optimization. Dataset correlations were then tested on key clinical outcome indicators to establish if routine data could be used as a reliable proxy measure for manual data. RESULTS: Forty-three patients were identified for the pilot study. The manual data showed a median age of 67 years (range 46- 89 years) and all patients had stage IIIA/B disease. Using the manual data, the median PFS was 10.78 months (range 1.58-37.49 months) and median OS was 16.36 months (range 2.69-37.49 months). Based on routine data, using proxy measures, the estimated median PFS was 10.68 months (range 1.61-31.93 months) and estimated median OS was 15.38 months (range 2.14-33.71 months). Overall, the routine data underestimated the PFS and OS of the manual data but there was good correlation with a Pearson correlati

Journal article

Williams M, Morton CE, 2018, Computational Medicine: Coding for Medics, Publisher: Elsevier, ISBN: 9780702076039

Book

Majewska P, Ioannidis S, Raza MH, Tanna N, Bulbeck H, Williams Met al., 2017, Postprogression survival in patients with glioblastoma treated with concurrent chemoradiotherapy: a routine care cohort study, CNS Oncology, Vol: 6, Pages: 307-313, ISSN: 2045-0907

Glioblastoma is the commonest malignant brain tumor in adults. Most patients develop progressive disease before they die. However, survival after developing progressive disease is infrequently reported. We identified patients with histologically proven disease who were treated with concurrent chemoradiotherapy during 2006–2013. We analyzed overall survival (OS), progression-free survival and postprogression survival (PPS) in relation to age, O6-methylguanine-DNA methyltransferase promoter methylation and extent of surgical resection. We identified 166 patients. Median survival was 13.5 months; 2-year OS was 21.7%. Median progression-free survival and PPS were 7.03 and 4.53 months, respectively. Age and extent of surgical resection were correlated with OS. Only the extent of surgical resection was associated with PPS. Our work suggests that the established prognostic factors for glioblastoma do not appear to help predict PPS.

Journal article

Kelly C, Majewska P, Ioannidis S, Raza MH, Williams Met al., 2017, Estimating progression-free survival in patients with glioblastoma using routinely collected data, Journal of Neuro-Oncology, Vol: 135, Pages: 621-627, ISSN: 0167-594X

Glioblastoma (GBM) represents 80% of all primarymalignant brain tumours in adults. Prognosis is poor,and there is a clear correlation between disease progressionand deterioration in functional status. In this pilot study weassess whether we can estimate disease progression andprogression free survival (PFS) from routinely collectedelectronic healthcare data. We identified fifty patients withglioblastoma who had chemo-radiotherapy. For each patientwe manually collected a reference data set recording demographics,surgery, radiotherapy, chemotherapy, follow-up anddeath. We also obtained an electronic routine data set for eachpatient by combining local data on chemotherapy/radiotherapyand hospital admissions. We calculated overall survival(OS) and PFS using the reference data set, and estimatedthem using the routine data sets using two different methods,and compared the estimated measures with the referencemeasures. Overall survival was 68% at 1 year and medianOS was 12.8 months. The routine data correctly identifiedprogressive disease in 37 of 40 patients and stable disease in 7 of 10 patients. PFS was 7.4 months and the estimated PFSusing routine data was 9.1 and 7.8 months with methods 1and 2 respectively. There was acceptable agreement betweenreference and routine data in 49 of 50 patients for OS and 35of 50 patients for PFS. The event of progression, subsequenttreatment and OS are well estimated using our approach, butPFS estimation is less accurate. Our approach could refineour understanding of the disease course and allow us to reportPFS, OS and treatment nationally.

Journal article

Williams M, Hommersom A, Butz R, Rabinowicz Set al., A Prognostic Model of Glioblastoma Multiforme Using Survival Bayesian Networks, Conference on Artificial Intelligence in Medicine in Europe, Publisher: Springer

Bayesian networks are attractive for developing prognostic models in medicine, due to the possibility for modelling the multivariate relationships between variables that come into play in the care process. In practice, the development of these models is hindered due to the fact that medical data is often censored, in particular the survival time. In this paper, we propose to directly integrate Cox proportional hazards models as part of a Bayesian network. Furthermore, we show how such Bayesian network models can be learned from data, after which these models can be used for probabilistic reasoning about survival. Finally, this method is applied to develop a prognostic model for Glioblastoma Multiforme, a common malignant brain tumour.

Conference paper

Williams M, Treasure P, Greenberg D, Brodbelt A, Collins Pet al., 2016, Surgeon volume and 30 day mortality for brain tumours in England, British Journal of Cancer, Vol: 115, Pages: 1379-1382, ISSN: 1532-1827

background: There is evidence that surgeons who perform more operations have better outcomes. However, in patients with brain tumours, all of the evidence comes from the USA.methods: We examined all English patients with an intracranial neoplasm who had an intracranial resection in 2008–2010. We included surgeons who performed at least six operations over 3 years, and at least one operation in the first and last 6 months of the period.results: The analysis data set comprised 9194 operations, 163 consultant neurosurgeons and 30 centres. Individual surgeon volumes varied widely (7–272; median=46). 72% of operations were on the brain, and 30 day mortality was 3%. A doubling of surgeon load was associated with a 20% relative reduction in mortality. Thirty day mortality varied between centres (0·95–8·62%) but was not related to centre workload.conclusions: Individual surgeon volumes correlated with patient 30 day mortality. Centres and surgeons in England are busier than surgeons and centres in the USA. There is no relationship between centre volume and 30 day mortality in England. Services in the UK appear to be adequately arranged at a centre level, but would benefit from further surgeon sub-specialisation.

Journal article

Mocanu A, Fan X, Toni F, Williams M, Chen Jet al., 2016, Online argumentation-based platform for recommending medical literature, 4th International Workshop, CIMA 2014, Publisher: Springer, Pages: 97-115, ISSN: 2190-3018

In medical practice, choosing the correct treatment is a key problem [1]. In this work, we present an online medical recommendation system, RecoMedic, that selects most relevant medical literature for patients. RecoMedic maintains a medical literature repository in which users can add new articles, query existing articles, compare articles and search articles guided by patient information. RecoMedic uses argumentation to accomplish the article selection. Thus, upon identifying relevant articles, RecoMedic also explains its selection. RecoMedic can be deployed using single-agent as well as multi-agent implementations. The developed system has been experimented with by senior medical Ph.D students from SouthernMedical University in China.

Conference paper

Williams M, Hunter A, 2016, Aggregation of Clinical Evidence Using Argumentation: A Tutorial Introduction, Foundations of Biomedical Knowledge Representation Methods and Applications, Editors: Hommersom, Lucas, Publisher: Springer, Pages: 317-337, ISBN: 9783319280073

We present a novel argumentation-based system for reasoning with the summarised results of clinical trials, and explore its use in a lung cancer context.

Book chapter

Williams M, Liu ZW, Hunter A, Macbeth Fet al., 2015, An updated systematic review of lung chemo-radiotherapy using a new evidence aggregation method, LUNG CANCER, Vol: 87, Pages: 290-295, ISSN: 0169-5002

Journal article

Brodbelt A, Greenberg D, Winters T, Williams M, Vernon S, Collins VPet al., 2015, Glioblastoma in England: 2007-2011, EUROPEAN JOURNAL OF CANCER, Vol: 51, Pages: 533-542, ISSN: 0959-8049

Journal article

Ricketts K, Williams M, Liu Z-W, Gibson Aet al., 2014, Automated estimation of disease recurrence in head and neck cancer using routine healthcare data, COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, Vol: 117, Pages: 412-424, ISSN: 0169-2607

Journal article

Williams M, Singer RA, Lerner A, 2014, A simple technique to estimate best- and worst-case survival in patients with metastatic colorectal cancer treated with chemotherapy, ANNALS OF ONCOLOGY, Vol: 25, Pages: 2014-2019, ISSN: 0923-7534

Journal article

Savage P, Sharkey R, Kua T, Schofield L, Richardson D, Panchmatia N, Papanastasopoulos P, Williams M, Falconer A, Power D, Arnold F, Ulbricht Cet al., 2014, Malignant spinal cord compression: NICE guidance, improvements and challenges., QJM : monthly journal of the Association of Physicians, Vol: 107, Pages: 277-82, ISSN: 1460-2393

BACKGROUND AND AIM: Malignant spinal cord compression (mSCC) is one of the most serious complications of cancer. Recent NICE guidance has aimed to improve patient pathways and outcomes for patients with mSCC. We have examined the current presentations, management and outcomes for patients with mSCC in West London following the implementation of the NICE guidance. MATERIALS AND METHODS: The electronic records and clinical notes were reviewed for all patients assessed for confirmed or potential mSCC at Charing Cross Hospital in 2012. Details on the number of referrals, the proportion with confirmed mSCC, the cancer diagnosis, treatment and outcome were analysed. RESULTS: 191 patients were reviewed with 127 (66%) cases of confirmed mSCC. The commonest tumour types were prostate cancer (26 cases), lung cancer (26), breast cancer (21) and kidney cancer (15). 21% of the patients had no previous cancer diagnosis; mSCC was their presenting diagnostic event. Radiotherapy was the predominant management, 24% of the patients had first line surgical treatment. At presentation 62% of patients were either chair or bed bound. Treatment brought important mobility benefits to all patients groups with 20% of the initially chair or bed bound patients leaving the hospital with independent mobility. CONCLUSION: Enhanced patients pathways with ease of access, rapid assessment and prompt treatment can improve outcomes. Despite these pathways many patients still present with gross motor impairment and over 20% have no previous diagnosis of cancer. Ongoing work to maintain awareness for patients and primary care of the diagnosis and emergency pathways is essential to optimize outcomes.

Journal article

Fan X, Toni F, Mocanu A, Williams Met al., 2014, Dialogical Two-Agent Decision Making with Assumption-based Argumentation, International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Publisher: ASSOC COMPUTING MACHINERY, Pages: 533-540

Conference paper

Craven R, Toni F, Williams M, 2014, Graph-based dispute derivations in assumption-based argumentation, Second International Workshop, TAFA 2013, Publisher: Springer, Pages: 46-62, ISSN: 0302-9743

Arguments in structured argumentation are usually defined as trees. This introduces both conceptual redundancy and inefficiency in standard methods of implementation. We introduce rule-minimal arguments and argument graphs to solve these problems, studying their use in assumption-based argumentation (ABA), a well-known form of structured argumentation. In particular, we define a new notion of graph-based dispute derivations for determining acceptability of claims under the grounded semantics in ABA, study formal properties and present an experimental evaluation thereof. © 2014 Springer-Verlag Berlin Heidelberg.

Conference paper

Craven R, Toni F, Williams M, 2014, Graph-based dispute derivations in assumption-based argumentation, Pages: 46-62, ISSN: 0302-9743

Arguments in structured argumentation are usually defined as trees. This introduces both conceptual redundancy and inefficiency in standard methods of implementation. We introduce rule-minimal arguments and argument graphs to solve these problems, studying their use in assumption-based argumentation (ABA), a well-known form of structured argumentation. In particular, we define a new notion of graph-based dispute derivations for determining acceptability of claims under the grounded semantics in ABA, study formal properties and present an experimental evaluation thereof. © 2014 Springer-Verlag Berlin Heidelberg.

Conference paper

Woolf DK, Williams M, Goh CL, Henderson DR, Menashy RV, Simpson N, Mastroianni B, Collis CHet al., 2013, Fractionated stereotactic radiotherapy for acoustic neuromas: long-term outcomes., Clinical oncology (Royal College of Radiologists (Great Britain)), Vol: 25, Pages: 734-8, ISSN: 1433-2981

AIMS: Acoustic neuromas are rare, benign intracranial tumours. There are a variety of treatment options, with no clear optimal management strategy and wide variation in treated outcomes. We report the outcomes from a 15 year cohort of patients treated at our centre using fractionated stereotactic radiotherapy (52.5 Gy in 25 fractions). MATERIALS AND METHODS: We analysed a retrospective case series. Patients were identified from patient records and a retrospective review of case notes and imaging reports was undertaken. We assessed tumour response using RECIST criteria and recorded toxicity. Progression-free survival was estimated using the Kaplan-Meier method. The study was conducted according to the STROBE guidelines. RESULTS: In total, 93 patients were identified; 83 patients had follow-up data, with a median follow-up period of 5.7 years. The overall control rate using RECIST criteria was 92%. Data on complications were available for 90 patients, with six (7%) experiencing a reduction in hearing, one (1%) developing trigeminal nerve dysfunction and one (1%) a deterioration in facial nerve function. Other toxicities included four (4%) patients who developed hydrocephalus, requiring the placement of a shunt and one (1%) patient who developed radiation brainstem necrosis. After further evaluation this patient was deemed to have been treated within acceptable dose constraints. CONCLUSION: These data suggest that a good control rate of acoustic neuromas is achievable using fractionated stereotactic radiotherapy to a dose of 52.5 Gy in 25 fractions. Toxicity is considered acceptable but the episode of radiation brainstem necrosis remains of concern and is the subject of further work.

Journal article

Williams M, Woolf D, Dickson J, Hughes R, Maher Jet al., 2013, Routine clinical data predict survival after palliative radiotherapy: an opportunity to improve end of life care., Clinical oncology (Royal College of Radiologists (Great Britain)), Vol: 25, Pages: 668-73, ISSN: 1433-2981

AIMS: Estimating the prognosis of cancer patients with incurable disease remains an important and difficult task for clinicians. Radiotherapy is a commonly used modality for palliation of symptoms, and we investigated whether we could predict differences in overall survival after the first course of palliative radiotherapy using routinely available data. MATERIALS AND METHODS: We examined variations in survival in 1226 patients after their first course of palliative radiotherapy in relation to cancer type, site treated, age, gender and socioeconomic status, and developed a multivariate model based on these. RESULTS: The median overall survival after the first course of palliative radiotherapy was 5.2 months. Large differences in survival were seen, depending on the primary tumour and the site treated. Survival was much better in those with breast (median overall survival 11.4 months) or prostate cancer (8.4 months, hazard ratio = 1.3) than in those with oesophageal/gastro-oesophageal junctional tumours (4.6 months, hazard ratio = 2.3) or lung (3.9 months, hazard ratio = 2.5). The treated site was an important prognostic factor (primary tumour versus bone metastases, hazard ratio = 1.3; versus brain metastases, hazard ratio = 2.1). CONCLUSIONS: The median overall survival after a first course of palliative radiotherapy was less than 6 months. Simple data, provided as part of routine radiotherapy practice, clearly discriminate between patients with very different prognoses. Such data could therefore be used to trigger appropriate end of life care.

Journal article

Liu Z-W, Fitzke H, Williams M, 2013, Using routine data to estimate survival and recurrence in head and neck cancer: our preliminary experience in twenty patients., Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery, Vol: 38, Pages: 334-9, ISSN: 1749-4486

Journal article

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