1,182 research outputs found

    Implementation of a parallel unstructured Euler solver on shared and distributed memory architectures

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    An efficient three dimensional unstructured Euler solver is parallelized on a Cray Y-MP C90 shared memory computer and on an Intel Touchstone Delta distributed memory computer. This paper relates the experiences gained and describes the software tools and hardware used in this study. Performance comparisons between two differing architectures are made

    Patch-based Convolutional Neural Network for Whole Slide Tissue Image Classification

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    Convolutional Neural Networks (CNN) are state-of-the-art models for many image classification tasks. However, to recognize cancer subtypes automatically, training a CNN on gigapixel resolution Whole Slide Tissue Images (WSI) is currently computationally impossible. The differentiation of cancer subtypes is based on cellular-level visual features observed on image patch scale. Therefore, we argue that in this situation, training a patch-level classifier on image patches will perform better than or similar to an image-level classifier. The challenge becomes how to intelligently combine patch-level classification results and model the fact that not all patches will be discriminative. We propose to train a decision fusion model to aggregate patch-level predictions given by patch-level CNNs, which to the best of our knowledge has not been shown before. Furthermore, we formulate a novel Expectation-Maximization (EM) based method that automatically locates discriminative patches robustly by utilizing the spatial relationships of patches. We apply our method to the classification of glioma and non-small-cell lung carcinoma cases into subtypes. The classification accuracy of our method is similar to the inter-observer agreement between pathologists. Although it is impossible to train CNNs on WSIs, we experimentally demonstrate using a comparable non-cancer dataset of smaller images that a patch-based CNN can outperform an image-based CNN

    Эффективность капецитабина по сравнению с 5-фторурацилом при раке толстой кишки и желудка: обновленный метаанализ выживаемости в шести клинических исследованиях

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    Оральный фторпиримидин — капецитабин — широко изучен в сравнительных исследованиях с вводимым внутривенно 5-фторурацилом как монотерапевтическое средство или в комплексном приме- нении при метастатическом колоректальном раке (МКРР) и метастатическом раке желудка (МРЖ). По рекомендации Европейских органов здравоохранения выполнен метаанализ эффективности применения капецитабина по сравнению с 5-фторурацилом при МКРР и МРЖ

    XELOX vs FOLFOX-4 as first-line therapy for metastatic colorectal cancer: NO16966 updated results

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    BACKGROUND: We report updated overall survival (OS) data from study NO16966, which compared capecitabine plus oxaliplatin (XELOX) vs 5-fluorouracil/folinic acid plus oxaliplatin (FOLFOX4) as first-line therapy in metastatic colorectal cancer. METHODS: NO16966 was a randomised, two-arm, non-inferiority, phase III comparison of XELOX vs FOLFOX4, which was subsequently amended to a 2 x 2 factorial design with further randomisation to bevacizumab or placebo. A planned follow-up exploratory analysis of OS was performed. RESULTS: The intent-to-treat (ITT) population comprised 2034 patients (two-arm portion, n = 634; 2 x 2 factorial portion, n 1400). For the whole NO16966 study population, median OS was 19.8 months in the pooled XELOX/XELOX-placebo/XELOX-bevacizumab arms vs 19.5 months in the pooled FOLFOX4/FOLFOX4-placebo/FOLFOX4-bevacizumab arms (hazard ratio 0.95 (97.5% CI 0.85-1.06)). In the pooled XELOX/XELOX-placebo arms, median OS was 19.0 vs 18.9 months in the pooled FOLFOX4/FOLFOX4-placebo arms (hazard ratio 0.95 (97.5% CI 0.83-1.09)). FOLFOX4 was associated with more grade 3/4 neutropenia/granulocytopenia and febrile neutropenia than XELOX, and XELOX with more grade 3 diarrhoea and grade 3 hand-foot syndrome than FOLFOX4. CONCLUSION: Updated survival data from study NO16966 show that XELOX is similar to FOLFOX4, confirming the primary analysis of progression-free survival. XELOX can be considered as a routine first-line treatment option for patients with metastatic colorectal cancer

    Epidemiology and natural history of central venous access device use and infusion pump function in the NO16966 trial

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    Background: Central venous access devices in fluoropyrimidine therapy are associated with complications; however, reliable data are lacking regarding their natural history, associated complications and infusion pump performance in patients with metastatic colorectal cancer.<p></p> Methods: We assessed device placement, use during treatment, associated clinical outcomes and infusion pump perfomance in the NO16966 trial.<p></p> Results: Device replacement was more common with FOLFOX-4 (5-fluorouracil (5-FU)+oxaliplatin) than XELOX (capecitabine+oxaliplatin) (14.1% vs 5.1%). Baseline device-associated events and post-baseline removal-/placement-related events occurred more frequently with FOLFOX-4 than XELOX (11.5% vs 2.4% and 8.5% vs 2.1%). Pump malfunctions, primarily infusion accelerations in 16% of patients, occurred within 1.6–4.3% of cycles. Fluoropyrimidine-associated grade 3/4 toxicity was increased in FOLFOX-4-treated patients experiencing a malfunction compared with those who did not (97 out of 155 vs 452 out of 825 patients), predominantly with increased grade 3/4 neutropenia (53.5% vs 39.8%). Febrile neutropenia rates were comparable between patient cohorts±malfunction. Efficacy outcomes were similar in patient cohorts±malfunction.<p></p> Conclusions: Central venous access device removal or replacement was common and more frequent in patients receiving FOLFOX-4. Pump malfunctions were also common and were associated with increased rates of grade 3/4 haematological adverse events. Oral fluoropyrimidine-based regimens may be preferable to infusional 5-FU based on these findings

    Association of progression-free survival with patient-reported outcomes and survival: results from a randomised phase 3 trial of panitumumab

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    In a randomised phase 3 trial, panitumumab significantly improved progression-free survival (PFS) in patients with refractory metastatic colorectal cancer (mCRC). This analysis characterises the association of PFS with CRC symptoms, health-related quality of life (HRQoL), and overall survival (OS). CRC symptoms (NCCN/FACT CRC symptom index, FCSI) and HRQoL (EQ-5D) were assessed for 207 panitumumab patients and 184 best supportive care (BSC) patients who had at least one post-baseline patient-reported outcome (PRO) assessment. Patients alive at week 8 were included in the PRO and OS analyses and categorised by their week 8 progression status as follows: no progressive disease (no PD; best response of at least stable disease) vs progressive disease (PD). Standard imputation methods were used to assign missing values. Significantly more patients were progression free at weeks 8–24 with panitumumab vs BSC. After excluding responders, a significant difference in PFS remained favouring panitumumab (HR=0.63, 95% CI=0.52–0.77; P<0.0001). At week 8, lack of disease progression was associated with significantly and clinically meaningful lower CRC symptomatology for both treatment groups and higher HRQoL for panitumumab patients only. Overall survival favoured no PD patients vs PD patients alive at week 8. Lack of disease progression was associated with better symptom control, HRQoL, and OS

    Surgery with curative-intent in patients treated with first-line chemotherapy plus bevacizumab for metastatic colorectal cancer First BEAT and the randomised phase-III NO16966 trial

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    BACKGROUND: Complete resection of metastases can result in cure for selected patients with metastatic colorectal cancer. METHODS: First BEAT evaluated the safety of bevacizumab with first-line chemotherapy in 1914 patients. Prospectively collected data from 225 patients who underwent curative-intent surgery were analysed, including an exploratory comparison of resection rate in patients treated with different regimens. NO16966 compared efficacy of oxaliplatin-based chemotherapy plus bevacizumab or placebo in 1400 patients. A retrospective analysis of resection rate was undertaken. RESULTS: In First BEAT, 225 out of 1914 patients (11.8%) underwent curative-intent surgery at median 64 days ( range 42-100) after the last dose of bevacizumab. R0 resection was achieved in 173 out of 225 patients (76.9%). There were no surgery-related deaths and serious post-operative complications were uncommon, with grade 3/4 bleeding and wound-healing events reported in 0.4% and 1.8%, respectively. Resection rates were highest in patients receiving oxaliplatin-based combination chemotherapy (P=0.002), possibly confounded by patient selection. In NO16966, 44 out of 699 patients treated with bevacizumab (6.3%) and 34 out of 701 patients treated with placebo (4.9%) underwent R0 metastasectomy (P=0.24). CONCLUSIONS: The rate of serious post-operative complications in First BEAT was comparable to historical controls without bevacizumab. In NO16966, there were no statistically significant differences in resection rates or overall survival in patients treated with bevacizumab vs placebo

    Exascale Deep Learning to Accelerate Cancer Research

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    Deep learning, through the use of neural networks, has demonstrated remarkable ability to automate many routine tasks when presented with sufficient data for training. The neural network architecture (e.g. number of layers, types of layers, connections between layers, etc.) plays a critical role in determining what, if anything, the neural network is able to learn from the training data. The trend for neural network architectures, especially those trained on ImageNet, has been to grow ever deeper and more complex. The result has been ever increasing accuracy on benchmark datasets with the cost of increased computational demands. In this paper we demonstrate that neural network architectures can be automatically generated, tailored for a specific application, with dual objectives: accuracy of prediction and speed of prediction. Using MENNDL--an HPC-enabled software stack for neural architecture search--we generate a neural network with comparable accuracy to state-of-the-art networks on a cancer pathology dataset that is also 16×16\times faster at inference. The speedup in inference is necessary because of the volume and velocity of cancer pathology data; specifically, the previous state-of-the-art networks are too slow for individual researchers without access to HPC systems to keep pace with the rate of data generation. Our new model enables researchers with modest computational resources to analyze newly generated data faster than it is collected.Comment: Submitted to IEEE Big Dat

    Challenges and solutions in the design and execution of the PROSPECT Phase II/III neoadjuvant rectal cancer trial (NCCTG N1048/Alliance)

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    Background: More than half of the 40,000 incident rectal cancer patients in the United States each year are diagnosed at clinical stage II and III (locally advanced stage). For this group, high rates of cure can be achieved with the combination of pelvic radiation and sensitizing 5-fluorouracil (chemoradiation), surgery and chemotherapy, but treatment is long, arduous and toxicities are substantial. The PROSPECT trial (N1048, NCT01515787) was designed to determine whether neoadjuvant chemotherapy with 5-fluorouracil and oxaliplatin (FOLFOX) could be used as an alternative to neoadjuvant chemoradiation without compromising treatment outcomes and to spare these patients excess toxicity. The statistical design balanced the twin co-primary goals of achieving low local and distant recurrence rates. Study design features contended with the need for stringent safeguards given limited phase II data, the need for straightforward criteria to facilitate both accrual and protocol fidelity and the importance of patients’ perspectives on symptom burden and treatment toxicity. Methods: PROSPECT is an ongoing multi-site two-group seamless phase II/III randomized trial comparing standard neoadjuvant chemoradiation versus neoadjuvant chemotherapy with selective use of chemoradiation for patients with locally advanced rectal cancer. Challenges addressed in the design and conduct of PROSPECT have included the following: (1) setting safety thresholds given limited single-center phase II data, (2) establishing workable eligibility criteria, (3) balancing competing time to local and distant recurrence as co-primary endpoints and (4) obtaining reliable and complete data for patients’ symptom burden. The design and implementation challenges, choices, modifications and their implications for the design of future national cooperative group clinical trials are presented. Results: PROSPECT incorporated stringent thresholds for both complete surgical resection (R0) and the time to local recurrence as early stopping rules. When predetermined stopping criteria were not met after evaluation of the first 366 participants in the randomized phase II, the study transitioned seamlessly to phase III with cumulative accrual of over 1000 participants. Eligibility criteria stipulating rectal tumor location based on distance from the anal verge were unworkable, and the protocol was amended to a more pragmatic approach that assigned surgeons with primary responsibility for determining eligibility. Central radiology review was feasible and in some cases prompted discontinuation of protocol treatment. Participation in toxicity reporting using the National Cancer Institute’s Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events was uniformly high and was well accepted by participants from over 200 sites in the United States, Canada and Switzerland. Conclusion: The strategies used to overcome these obstacles may inform the design of other studies that involve multi-modality treatment interventions, particularly trials where implementation of consistent criteria for eligibility and outcomes across hundreds of practice settings is necessary
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