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The ectonucleotidases CD39 and CD73 are present on immune cells and play important roles in cancer progression by suppressing antitumour immunity. As such, CD39 and CD73 on peripheral blood mononuclear cells (PBMCs) are emerging as potential biomarkers to predict disease outcomes and treatment responses in cancer patients. This study aimed to examine T and B cells, including CD39 and CD73 expressing subsets, by flow cytometry in PBMCs from 28 patients with head and neck squamous cell carcinoma (HNSCC) and to assess the correlation with the treatment modality, human papillomavirus (HPV) status, and relapse-free survival (RFS). The PBMCs were examined pre-, mid-, and post-radiotherapy with concurrent cisplatin chemotherapy or anti-epidermal growth factor receptor antibody (cetuximab) therapy. Combination radiotherapy caused changes to T and B cell populations, including CD39 and CD73 expressing subsets, but no such differences were observed between concurrent chemotherapy and cetuximab. Pretreatment PBMCs from HPV+ patients contained increased proportions of CD39−CD73−CD4+ T cells and reduced proportions of CD39−/+CD73+CD4+ T cells compared to the equivalent cells from HPV− patients. Notably, the pretreatment CD4+:CD8+ T cell ratios and CD39+CD73+CD19+ B cell proportions below the respective cohort medians corresponded with an improved RFS. Collectively, this study supports the notion that CD39 and CD73 may contribute to disease outcomes in HNSCC patients and may assist as biomarkers, either alone or as part of immune signatures, in HNSCC. Further studies of CD39 and CD73 on PBMCs from larger cohorts of HNSCC patients are warranted.

Background/Aim Right sided colon cancer (RsCC) is proposed to be a distinct disease entity to left sided colon cancer (LsCC). We seek to confirm primary tumour location as an independent prognostic factor in locoregional colorectal cancer. Methods All patients with stage I – III primary adenocarcinoma of colon were identified from the New South Wales (NSW) clinical cancer registry (2006–2013). Primary tumour location (RsCC vs LsCC) survival analyses were conducted using the Kaplan-Meier method, and adjusted hazard ratios for 5-year all-cause mortality (OS) and 5-year cancer specific mortality (CSS) were obtained using Cox proportional hazards regression. Results We identified 9509 patients including 5051 patients with RsCC and 4458 with LsCC. Patients with RsCC were more likely to be older, female, have a higher Charlson comorbidity index, and have worse tumour prognostic factors. In univariate analysis of all stages combined, those patients with RsCC had a worse overall survival (OS, HR 1.20 95% CI 1.11–1.29, p  < 0.0001), although this was not significant in the multivariate analysis (HR 0.96 95% CI 0.89–1.04, p  = 0.35). Stage I patients with RsCC had a trend to improved OS (multivariate HR 0.84 95% CI 0.69–1.01, p  = 0.07) and a significantly improved CSS (multivariate HR 0.51 95% CI 0.35–0.75, p  = 0.0006). In stage II patients with RsCC there was a significantly improved OS (multivariate HR 0.85 95% CI 0.75–0.98, p  = 0.02) and CSS (multivariate HR 0.59 95% CI 0.45–0.78, p  = 0.0002) compared to LsCC. In stage III patients, those with RsCC had a worse OS (multivariate HR 1.13 95% CI 1.01–1.26, p  = 0.032) and a trend to worse CSS (multivariate HR 1.12 95% CI 0.94–1.33, p  = 0.22). Conclusions Primary tumour location is an important prognostic factor in locoregional colon cancer with an effect that varies by stage. RsCC is associated with lower all-cause mortality in stage II, and higher all-cause mortality in stage III.

Despite the acceptability and efficacy of e-patient-reported outcome (ePRO) systems, implementation in routine clinical care remains challenging. This pragmatic trial implemented the PROMPT-Care (Patient Reported Outcome Measures for Personalized Treatment and Care) web-based system into existing clinical workflows and evaluated its effectiveness among a diverse population of patients with cancer. Adult patients with solid tumors receiving active treatment or follow-up care in four cancer centers were enrolled. The PROMPT-Care intervention supported patient management through (1) monthly off-site electronic PRO physical symptom and psychosocial well-being assessments, (2) automated electronic clinical alerts notifying the care team of unresolved clinical issues following two consecutive assessments, and (3) tailored online patient self-management resources. Propensity score matching was used to match controls with intervention patients in a 4:1 ratio for patient age, sex, and treatment status. The primary outcome was a reduction in emergency department presentations. Secondary outcomes were time spent on chemotherapy and the number of allied health service referrals. From April 2016 to October 2018, 328 patients from four public hospitals received the intervention. Matched controls (n=1312) comprised the general population of patients with cancer, seen at the participating hospitals during the study period. Emergency department visits were significantly reduced by 33% (P=.02) among patients receiving the intervention compared with patients in the matched controls. No significant associations were found in allied health referrals or time to end of chemotherapy. At baseline, the most common patient reported outcomes (above-threshold) were fatigue (39%), tiredness (38.4%), worry (32.9%), general wellbeing (32.9%), and sleep (24.1%), aligning with the most frequently accessed self-management domain pages of physical well-being (36%) and emotional well-being (23%). The majority of clinical feedback reports were reviewed by nursing staff (729/893, 82%), largely in response to the automated clinical alerts (n=877). Algorithm-supported web-based systems utilizing patient reported outcomes in clinical practice reduced emergency department presentations among a diverse population of patients with cancer. This study also highlighted the importance of (1) automated triggers for reviewing above-threshold results in patient reports, rather than passive manual review of patient records; (2) the instrumental role nurses play in managing alerts; and (3) providing patients with resources to support guided self-management, where appropriate. Together, these factors will inform the integration of web-based PRO systems into future models of routine cancer care. Australian New Zealand Clinical Trials Registry ACTRN12616000615482; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370633. RR2-10.1186/s12885-018-4729-3.

The metallic fixations used in surgical procedures to support the spine mechanically usually consist of high‐density materials. Radiation therapy to palliate spinal cord compression can include prophylactic inclusion of potential tumor around the site of such fixation devices. Determination of the correct density and shape of the spine fixation device has a direct effect on the dose calculation of the radiation field. Even with the application of modern computed tomography (CT), under‐ or overestimation of dose, both immediately next to the device and in the surrounding tissues, can occur due to inaccuracies in the dose prediction algorithm. In this study, two commercially available dose prediction algorithms (Eclipse AAA and ACUROS), EGSnrc Monte Carlo, and GAFchromic film measurements were compared for a clinical spine SBRT case to determine their accuracy. An open six‐field plan and a clinical nine‐field IMRT plan were applied to a phantom containing a metal spine fixation device. Dose difference and gamma analysis were performed in and around the tumor region adjacent to the fixation device. Dose calculation inconsistency was observed in the open field plan. However, in the IMRT plan, the dose perturbation effect was not observed beyond 5 mm. Our results suggest that the dose effect of the metal fixation device to the spinal cord and the tumor volume is not observable, and all dose calculation algorithms evaluated can provide clinically acceptable accuracy in the case of spinal SBRT, with the tolerance of 95% for gamma criteria of 3%/3 mm. PACS number(s): 87.53.bn, 87.53.Ly, 87.55.kd

The main objective of this study is to demonstrate the performance characteristics of the Magic Plate (MP) system when operated upstream of the patient in transmission mode (MPTM). The MPTM is an essential component of a real‐time QA system designed for operation during radiotherapy treatment. Of particular interest is a quantitative study into the influence of the MP on the radiation beam quality at several field sizes and linear accelerator potential differences. The impact is measured through beam perturbation effects such as changes in the skin dose and/or percentage depth dose (PDD) (both in and out of field). The MP was placed in the block tray of a Varian linac head operated at 6, 10 and 18 MV beam energy. To optimize the MPTM operational setup, two conditions were investigated and each setup was compared to the case where no MP is positioned in place (i.e., open field): (i) MPTM alone and (ii) MPTM with a thin passive contamination electron filter. The in‐field and out‐of‐field surface doses of a solid water phantom were investigated for both setups using a Markus plane parallel (Model N23343) and Attix parallel‐plate, MRI model 449 ionization chambers. In addition, the effect on the 2D dose distribution measured by the Delta4 QA system was also investigated. The transmission factor for both of these MPTM setups in the central axis was also investigated using a Farmer ionization chamber (Model 2571A) and an Attix ionization chamber. Measurements were performed for different irradiation field sizes of 5×5 cm2 and 10×10 cm2. The change in the surface dose relative to dmax was measured to be less than 0.5% for the 6 MV, 10 MV, and 18 MV energy beams. Transmission factors measured for both set ups (i & ii above) with 6 MV, 10 MV, and 18 MV at a depth of dmax and a depth of 10 cm were all within 1.6% of open field. The impact of both the bare MPTM and the MPTM with 1 mm buildup on 3D dose distribution in comparison to the open field investigated using the Delta4 system and both the MPTM versions passed standard clinical gamma analysis criteria. Two MPTM operational setups were studied and presented in this article. The results indicate that both versions may be suitable for the new real‐time megavoltage photon treatment delivery QA system under development. However, the bare MPTM appears to be slightly better suited of the two MP versions, as it minimally perturbs the radiation field and does not lead to any significant increase in skin dose to the patient. PACS number(s): 87.50.up, 87.53.Bn, 87.55.N, 87.55.Qr, 87.56.Fc.

The aims of this work were to establish a program to fit NTCP models to clinical data with multiple toxicity endpoints, to test the method using a realistic test dataset, to compare three methods for estimating confidence intervals for the fitted parameters and to characterise the speed and performance of the program.

Patient-reported outcome (PRO) measures have been used widely to screen for depression, anxiety, and symptoms in cancer patients. Computer-based applications that collect patients' responses and transfer them to the treating health professional in real time have the potential to improve patient well-being and cancer outcomes. This study will test the feasibility and acceptability of a newly developed eHealth system which facilitates PRO data capture from cancer patients, data linkage and retrieval to support clinical decisions and patient self-management, and data retrieval to support ongoing evaluation and innovative research. The eHealth system is being developed in consultation with 3 overarching content-specific expert advisory groups convened for this project: the clinical advisory group, technical advisory group, and evaluation advisory group. The following work has already been completed during this phase of the study: the Patient-Reported Outcome Measures for Personalized Treatment and Care (PROMPT-Care) eHealth system was developed, patient-reported outcomes were selected (distress, symptoms, unmet needs), algorithms to inform intervention thresholds for clinical and self-management were determined, clinician PRO feedback summary and longitudinal reports were designed, and patient self-management resources were collated. PROsaiq, a custom information technology system, will transfer PRO data in real time into the hospital-based oncology information system to support clinical decision making. The PROMPT-Care system feasibility and acceptability will be assessed through patients completing PROMPT-Care assessments, participating in face-to-face cognitive interviews, and completing evaluation surveys and telephone interviews and oncology staff participating in telephone interviews. Over the course of 3 months, the system will be pilot-tested with up to 50 patients receiving treatment or follow-up care and 6 oncology staff at 2 hospitals in New South Wales, Australia. Data will be collected to determine the accuracy and completeness of data transfer procedures, extent of missing data from participants' assessments, acceptability of the eHealth system and usefulness of the self-management resources (via patient evaluation surveys and interviews), and acceptability and perceived usefulness of real-time PRO reporting (via oncology staff interviews) at the completion of the pilot phase. This research investigates implementation of evidence into real world clinical practice through development of an efficient and user-friendly eHealth system. This study of feasibility and acceptability of the newly developed eHealth system will inform the next stage of larger scale testing and future implementation of the system as part of routine care. Australian New Zealand Clinical Trials Registry ACTRN1261500135294; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=369299&isReview=true (Archived by WebCite at http://www.webcitation.org/6lzylG5A0).

Circulating tumour cell (CTC) enumeration and profiling has been established as a valuable clinical tool in many solid malignancies. A key challenge in CTC research is the limited number of cells available for study. Ex vivo CTC culture permits expansion of these rare cell populations for detailed characterisation, functional assays including drug sensitivity testing, and investigation of the pathobiology of metastases. We report for the first time the establishment and characterisation of two continuous CTC lines from patients with gastroesophageal cancer. The two cell lines (designated UWG01CTC and UWG02CTC) demonstrated rapid tumorigenic growth in immunodeficient mice and exhibit distinct genotypic and phenotypic profiles which are consistent with the tumours of origin. UWG02CTC exhibits an EpCAM+, cytokeratin+, CD44+ phenotype, while UWG01CTC, which was derived from a patient with metastatic neuroendocrine cancer, displays an EpCAM−, weak cytokeratin phenotype, with strong expression of neuroendocrine markers. Further, the two cell lines show distinct differences in drug and radiation sensitivity which match differential cancer-associated gene expression pathways. This is strong evidence implicating EpCAM negative CTCs in metastasis. These novel, well characterised, long-term CTC cell lines from gastroesophageal cancer will facilitate ongoing research into metastasis and the discovery of therapeutic targets.

Purpose We introduce the next generation of “MagicPlate” 2D monolithic pixelated semiconductor detectors – MagicPlate‐976 (MP976). It features a larger array area, higher spatial resolution, and does not require external triggering. We perform a comprehensive characterization for small‐field steep‐dose‐gradient dosimetry applications in radiation therapy focusing on x‐ray beams used in stereotactic treatments. Methods The MP976, developed by the Centre for Medical Radiation Physics, consists of 976 ion‐implanted diodes on a thin n‐type epitaxial silicon substrate with a total array area of 58 × 58 mm2. The central region has “small” diodes with an area of 0.2 × 0.2 mm2 and 1 mm pitch and the peripheral region has “large” diodes with an area of 0.6 × 0.6 mm2 and 2 mm pitch. The detector was primed with 10 kGy (Co‐60) and tested using a Varian TrueBeam linear accelerator for sensitivity change and dose linearity, and variations in response due to dose‐per‐pulse and beam incidence angle. Output factors, depth dose, and beam profiles were measured and compared with reference data. Results After the 10 kGy, the sensitivity declined by (74 ± 5)% for “large” diodes and by (78 ± 7)% for the “small” ones, the dose‐per‐pulse (DPP) dependence was in the range of commercially available diodes, however, a difference in the DPP dependence between the “large” and “small” diodes of (8.4 ± 0.2)% was found in the studied DPP range from 0.131–1.111 mGy/pulse. The minimum angular response was at 90° for 6 MV and 100° for 10 MV flattened beams (76% and 82%, respectively). The output factors and depth dose response showed agreement with the reference within 3.1% and 1%, respectively. Deviation in small field 80%/20% penumbra measurements was within 0.5 mm for 6 MV FF and 0.3 mm for 10 MV FFF. Full width at half maximum (FWHM) for the beam profiles agreed within 0.5 mm for both beam qualities. Conclusion The new MagicPlate‐976 detector system is shown to be suitable for dosimetry in small fields and steep dose gradients. It provides 1 mm spatial resolution in the central region and 2 mm on the periphery and has no dependence on the field size. The system's high spatial and temporal resolution opens new opportunities for trigger‐less, film‐less, and time‐resolved verification and error identification for complex stereotactic treatment plans.

In progressing the use of big data in health systems, standardised nomenclature is required to enable data pooling and analyses. In many radiotherapy planning systems and their data archives, target volumes (TV) and organ-at-risk (OAR) structure nomenclature has not been standardised. Machine learning (ML) has been utilised to standardise volumes nomenclature in retrospective datasets. However, only subsets of the structures have been targeted. Within this paper, we proposed a new approach for standardising all the structures nomenclature by using multi-modal artificial neural networks. A cohort consisting of 1613 breast cancer patients treated with radiotherapy was identified from Liverpool & Macarthur Cancer Therapy Centres, NSW, Australia. Four types of volume characteristics were generated to represent each target and OAR volume: textual features, geometric features, dosimetry features, and imaging data. Five datasets were created from the original cohort, the first four represented different subsets of volumes and the last one represented the whole list of volumes. For each dataset, 15 sets of combinations of features were generated to investigate the effect of using different characteristics on the standardisation performance. The best model reported 99.416% classification accuracy over the hold-out sample when used to standardise all the nomenclatures in a breast cancer radiotherapy plan into 21 classes. Our results showed that ML based automation methods can be used for standardising naming conventions in a radiotherapy plan taking into consideration the inclusion of multiple modalities to better represent each volume.