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• CDK4/6 inhibitors represent the standard-of-care for metastatic HR+/HER2 breast cancer. • Available data on CDK4/6 inhibitors and concomitant RT are conflicting. • We showed that concurrent RT did not increase treatments severe toxicity. • A consensus guideline to help physician's routine practice is strongly needed. Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) currently represent the standard of care for the initial treatment of patients with metastatic hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer. The aim of our study is to evaluate the safety of the use of concomitant radiation therapy (RT) in a consecutive series of HR+/HER2- patients treated in two academic institutions with CDK4/6i in the metastatic setting. From September 2017 to February 2020, we retrospectively collected and analysed data on a sequential series of patients treated with CDK4/6i, receiving RT or not, at two European institutions. Primary outcome of the study was the association between RT and any adverse events (AEs) ≥ G3. Secondary outcomes were the association between RT and any AEs (any grade), CDK4/6i dose reduction rate, and CDK4/6i treatment discontinuation rate. We analysed a total of 132 consecutive women; RT was prescribed in 57 (43.2%) patients (70 irradiated lesions). The median age of the series was 52.1 years (range 32.3–78.2). Concomitant RT administration was not significantly related to higher AEs ≥ G3 (p = 0.19) and any grade AEs (p = 1.0); there was no association with RT and CDK4/6i dose reduction (p = 0.49) and discontinuation rates (p = 0.14). At a median follow-up of 18.8 months, the progression-free survival (PFS) rate was 35% and the overall survival (OS) rate was 38.7% in the whole group. The use of concomitant RT did not affect both PFS (p = 0.71) and OS rates (p = 0.55). Our data are encouraging regarding the safety of this combination, showing that concurrent RT did not increase severe toxicity and did not have an impact on systemic treatment conduction. [ABSTRACT FROM AUTHOR]

We describe a new, low-cost system designed to provide multi-sensor remote condition monitoring of modern scientific laboratories and to allow users to perform actions from remote locations in the case of detection of specified events. The system is battery operated and does not require the presence of a local area network or WiFi (which are typically not available in the case of, e.g., power losses), as it exploits the growing infrastructure of Internet of Things low-power wide area networks. In particular, our system exploits the new SigFox ultra-narrow-bandwidth infrastructure and provides a bidirectional link between the instrumentation and the remote user even in the case of power line outages, which are among the most critical situations that a scientific laboratory can withstand. The system can detect the occurrence of predefined events in very short times and autonomously react with a series of predefined actions, also allowing a remote user to timely perform additional actions on the system through a user-friendly smartphone application or via a browser interface. The system also embeds a novel power loss detection architecture, which detects power line failures in less than 2 ms. We provide a full characterization of the prototype, including reaction times, connection latencies, sensor sensitivity, and power consumption. [ABSTRACT FROM AUTHOR]

Abstract Aim We present the final results of the BONADIUV trial, a single-blind, randomised, placebo-controlled phase 2 study to evaluate the impact of ibandronate treatment on bone mineral density (BMD) in osteopenic women taking aromatase inhibitors (AI). Patients and methods Between 2011 and 2014, 171 osteopenic patients were randomised in a 1:1 ratio to receive either placebo or oral monthly ibandronate (150 mg). Treatment duration was 2 years, with 6-month evaluation. Primary end-point was the 2-year lumbar spine (LS) and total hip (TH) T-score mean differences as measure of BMD variation. Secondary analyses of survival outcomes have been performed at a 5-year median follow-up. ClinicalTrials.gov identifier NCT02616744. Results Median age of study population was 60.2 years (range 44–75). At the database cut-off time, the median follow-up was 63.3 months (range 2.7–87.3). No difference in terms of T-score was shown at baseline between arms both for TH (P = 0.61) and LS (P = 0.96). At 2-year follow up, the mean change was statistically significant in favour of ibandronate arm both at TH (P = 0.0002) and LS (P < 0.0001). No significant difference in terms of adverse events was observed between arms. At a median follow-up of 63.3 months (range 2.7–87.3), the overall survival (OS) rate was 97.5% in the placebo group and 93.0% in the ibandronate arm (P = 0.19). The invasive disease-free survival (iDFS) rates did not differ between groups (P = 0.42). Conclusions Ibandronate compared to placebo improved BMD change in osteopenic women treated with adjuvant AI. Five-year survival analyses showed no difference between arms in terms of OS and iDFS rates. Highlights • Bisphosphonates prevent bone loss in adjuvant osteopenic breast cancer patients. • A bone loss prevention strategy for patients receiving adjuvant AI is crucial. • Longer follow-up and further investigations are warranted. [ABSTRACT FROM AUTHOR]

Representing patterns as labeled graphs is becoming increasingly common in the broad field of computational intelligence. Accordingly, a wide repertoire of pattern recognition tools, such as classifiers and knowledge discovery procedures, are nowadays available and tested for various datasets of labeled graphs. However, the design of effective learning procedures operating in the space of labeled graphs is still a challenging problem, especially from the computational complexity viewpoint. In this paper, we present a major improvement of a general-purpose classifier for graphs, which is conceived on an interplay between dissimilarity representation, clustering, information-theoretic techniques, and evolutionary optimization algorithms. The improvement focuses on a specific key subroutine devised to compress the input data. We prove different theorems which are fundamental to the setting of the parameters controlling such a compression operation. We demonstrate the effectiveness of the resulting classifier by benchmarking the developed variants on well-known datasets of labeled graphs, considering as distinct performance indicators the classification accuracy, computing time, and parsimony in terms of structural complexity of the synthesized classification models. The results show state-of-the-art standards in terms of test set accuracy and a considerable speed-up for what concerns the computing time. [ABSTRACT FROM AUTHOR]

Goal: We analyze 48 signals of rest tremor velocity related to 12 distinct subjects affected by the Parkinson's disease. The subjects belong to two different groups, high- and low-amplitude rest tremors, with four and eight subjects, respectively. Each subject has been tested in four settings given by combining the use of deep brain stimulation and L-DOPA medication. Methods: We develop two main feature-based representations of the signals, which are obtained by considering 1) the long-term correlations and multifractal properties, and 2) the power spectra. Results: Our results show that, when medication is used, a qualitative change is observed in the related signals from anticorrelated to long term positively correlated. In addition, the medication effect yields statistically significant differences in both high- and low-amplitude tremor groups. We successively consider three different classification problems, involving the recognition of 1) the use of medication, 2) the use of deep brain stimulation, and 3) the membership to the high- and low-amplitude tremor groups. Classification results show that the best results are obtained with a parsimonious, two-dimensional (2-D) representation encoding the long-term correlations and multifractal properties of the signals. Conclusions: Long-term correlations and multifractal signatures of time series provided an effective tool to analyze Parkinsonian rest tremor signals. Significance: The developed 2-D representation is a parsimonious and effective representation for rest tremor signals that could be adopted in clinical settings, even by considering resource-constrained scenarios. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a density-based clusters' representatives selection algorithm that identifies the most central patterns from the dense regions in the dataset. The method, which has been implemented using two different strategies, is applicable to input spaces with no trivial geometry. Our approach exploits a probability density function built through the Parzen estimator, which relies on a (not necessarily metric) dissimilarity measure. Being a representatives extractor a general-purpose algorithm, our method is obviously applicable in different contexts. However, to test the proposed procedure, we specifically consider the problem of initializing the k-means algorithm. We face problems defined on standard real-valued vectors, labeled graphs, and finally sequences of real-valued vectors and sequences of characters. The obtained results demonstrate the effectiveness of the proposed representative selection method with respect to other state-of-the-art solutions. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a machine learning methodology for localising the seizure onset zone in subjects with epilepsy. We represent brain states as functional networks obtained from intracranial electroencephalography recordings, using correlation and the phase-locking value to quantify the coupling between different brain areas. Our method is based on graph neural networks (GNNs) and the attention mechanism, two of the most significant advances in artificial intelligence in recent years. Specifically, we train a GNN to distinguish between functional networks associated with interictal and ictal phases. The GNN is equipped with an attention-based layer that automatically learns to identify those regions of the brain (associated with individual electrodes) that are most important for a correct classification. The localisation of these regions does not require any prior information regarding the seizure onset zone. We show that the regions of interest identified by the GNN strongly correlate with the localisation of the seizure onset zone reported by electroencephalographers. We report results both for human patients and for simulators of brain activity. We also show that our GNN exhibits uncertainty for those patients for which the clinical localisation was unsuccessful, highlighting the robustness of the proposed approach. • We present a new method for seizure localisation in subjects with epilepsy. • Our method is based on graph neural networks (GNNs) with an attentional layer. • The attention scores of the GNN predict the clinically-identified seizure onset zones. • In uncertain clinical outcomes, our GNN also shows uncertainty in the localisation. • Our method works well even in the case of small training datasets available. [ABSTRACT FROM AUTHOR]

In this paper, we study long-term correlations and multifractal properties elaborated from time series of three-phase current signals from an industrial electric arc furnace. Implicit sinusoidal trends are suitably detected by considering the scaling of the fluctuation functions. Time series are then filtered via a Fourier-based analysis to remove such strong periodicities. In the filtered time series we detected long-term, positive correlations. The presence of positive correlations is in agreement with the typical V-I characteristic (hysteresis) of the electric arc furnace, thus providing a sound physical justification for the memory effects found in the current time series. The multifractal signature is strong enough in the filtered time series to be effectively classified as multifractal. [ABSTRACT FROM AUTHOR]

In this paper, we study the structure and dynamical properties of protein contact networks with respect to other biological networks, together with simulated archetypal models acting as probes. We consider both classical topological descriptors, such as modularity and statistics of the shortest paths, and different interpretations in terms of diffusion provided by the discrete heat kernel, which is elaborated from the normalized graph Laplacians. A principal component analysis shows high discrimination among the network types, by considering both the topological and heat kernel based vector characterizations. Furthermore, a canonical correlation analysis demonstrates the strong agreement among those two characterizations, providing thus an important justification in terms of interpretability for the heat kernel. Finally, and most importantly, the focused analysis of the heat kernel provides a way to yield insights on the fact that proteins have to satisfy specific structural design constraints that the other considered networks do not need to obey. Notably, the heat trace decay of an ensemble of varying-size proteins denotes subdiffusion, a peculiar property of proteins. [ABSTRACT FROM AUTHOR]

Detecting faults in electrical power grids is of paramount importance, both from the electricity operator and consumer point of view. Modern electric power grids (smart grids) are equipped with smart sensors that allow to gather real-time information regarding the physical status of all components belonging to the whole infrastructure (e.g., cables and related insulation, transformers, and breakers). In real-world smart grid systems, usually, additional information that are related to the operational status of the grid are collected, such as meteorological information. Designing an efficient recognition model to discriminate faults in real-world smart grid system is hence a challenging task. This follows from the heterogeneity of the information that actually determine a typical fault condition. In this paper, we deal with the problem of modeling and recognizing faults in a real-world smart grid system, which supplies the entire city of Rome, Italy. Recognition of faults is addressed by following a combined approach of dissimilarity measures learning and one-class classification techniques. We provide here an in-depth study related to the available data and to the models based on the proposed one-class classification approach. Furthermore, we perform a comprehensive analysis of the fault recognition results by exploiting a fuzzy set based decision rule. [ABSTRACT FROM AUTHOR]

Researches in granular modeling produced a variety of mathematical models, such as intervals (higher-order) fuzzy sets, rough sets, and shadowed sets, which are all suitable to characterize the so-called information granules. Modeling of the input data uncertainty is recognized as a crucial aspect in information granulation. Moreover, the uncertainty is a well-studied concept in many mathematical settings, such as those of probability theory, fuzzy set theory, and possibility theory. This fact suggests that an appropriate quantification of the uncertainty expressed by the information granule model could be used to define an invariant property, to be exploited in practical situations of information granulation. In this perspective, we postulate that a procedure of information granulation is effective if the uncertainty conveyed by the synthesized information granule is in a monotonically increasing relation with the uncertainty of the input data. In this paper, we present a data granulation framework that elaborates over the principles of uncertainty introduced by Klir. Being the uncertainty a mesoscopic descriptor of systems and data, it is possible to apply such principles regardless of the input data type and the specific mathematical setting adopted for the information granules. The proposed framework is conceived (i) to offer a guideline for the synthesis of information granules and (ii) to build a groundwork to compare and quantitatively judge over different data granulation procedures. To provide a suitable case study, we introduce a new data granulation technique based on the minimum sum of distances, which is designed to generate type-2 fuzzy sets. The automatic membership function elicitation is completely based on the dissimilarity values of the input data, which makes this approach widely applicable. We analyze the procedure by performing different experiments on two distinct data types: feature vectors and labeled graphs. Results show that the uncertainty of the input data is suitably conveyed by the generated type-2 fuzzy set models. [ABSTRACT FROM AUTHOR]

The multifractal detrended fluctuation analysis of time series is able to reveal the presence of long-range correlations and, at the same time, to characterize the self-similarity of the series. The rich information derivable from the characteristic exponents and the multifractal spectrum can be further analyzed to discover important insights into the underlying dynamical process. In this paper, we employ multifractal analysis techniques in the study of protein contact networks. To this end, initially a network is mapped to three different time series, each of which is generated by a stationary unbiased random walk. To capture the peculiarities of the networks at different levels, we accordingly consider three observables at each vertex: the degree, the clustering coefficient, and the closeness centrality. To compare the results with suitable references, we consider also instances of three well-known network models and two typical time series with pure monofractal and multifractal properties. The first result of notable interest is that time series associated to protein contact networks exhibit long-range correlations (strong persistence), which are consistent with signals in-between the typical monofractal and multifractal behavior. Successively, a suitable embedding of the multifractal spectra allows to focus on ensemble properties, which in turn gives us the possibility to make further observations regarding the considered networks. In particular, we highlight the different role that small and large fluctuations of the considered observables play in the characterization of the network topology. [ABSTRACT FROM AUTHOR]

We evaluate a version of the recently-proposed classification system named Optimized Dissimilarity Space Embedding (ODSE) that operates in the input space of sequences of generic objects. The ODSE system has been originally presented as a classification system for patterns represented as labeled graphs. However, since ODSE is founded on the dissimilarity space representation of the input data, the classifier can be easily adapted to any input domain where it is possible to define a meaningful dissimilarity measure. Here we demonstrate the effectiveness of the ODSE classifier for sequences by considering an application dealing with the recognition of the solubility degree of the Escherichia coli proteome. Solubility, or analogously aggregation propensity, is an important property of protein molecules, which is intimately related to the mechanisms underlying the chemicophysical process of folding. Each protein of our dataset is initially associated with a solubility degree and it is represented as a sequence of symbols, denoting the 20 amino acid residues. The herein obtained computational results, which we stress that have been achieved with no context-dependent tuning of the ODSE system, confirm the validity and generality of the ODSE-based approach for structured data classification. [ABSTRACT FROM AUTHOR]

Accelerated partial breast irradiation (APBI) has been introduced as an alternative treatment method for selected patients with early stage breast cancer (BC). Intensity-modulated radiotherapy (IMRT) has the theoretical advantage of a further increase in dose conformity compared with three-dimensional techniques, with more normal tissue sparing. The aim of this randomised trial is to compare the local recurrence and survival of APBI using the IMRT technique after breast-conserving surgery to conventional whole-breast irradiation (WBI) in early stage BC. This study was performed at the University of Florence (Florence, Italy). Women aged more than 40 years affected by early BC, with a maximum pathological tumour size of 25 mm, were randomly assigned in a 1:1 ratio to receive either WBI or APBI using IMRT. Patients in the APBI arm received a total dose of 30 Gy to the tumour bed in five daily fractions. The WBI arm received 50 Gy in 25 fractions, followed by a boost on the tumour bed of 10 Gy in five fractions. The primary end-point was occurrence of ipsilateral breast tumour recurrences (IBTRs); the main analysis was by intention-to-treat. This trial is registered with ClinicalTrials.gov, number NCT02104895. A total of 520 patients were randomised (260 to external WBI and 260 to APBI with IMRT) between March 2005 and June 2013. At a median follow-up of 5.0 years (Interquartile Range (IQR) 3.4–7.0), the IBTR rate was 1.5% (three cases) in the APBI group (95% confidence interval (CI) 0.1–3.0) and in the WBI group (three cases; 95% CI 0.0–2.8). No significant difference emerged between the two groups (log rank test p = 0.86). We identified seven deaths in the WBI group and only one in the APBI group (p = 0.057). The 5-year overall survival was 96.6% for the WBI group and 99.4% for the APBI group. The APBI group presented significantly better results considering acute (p = 0.0001), late (p = 0.004), and cosmetic outcome (p = 0.045). To our knowledge, this is the first randomised study using the IMRT technique for APBI delivery. No significant difference in terms of IBTR and overall survival was observed between the two arms. APBI displayed a significantly better toxicity profile. [ABSTRACT FROM AUTHOR]

Background Accelerated partial breast irradiation (APBI) has been introduced as an alternative treatment method for selected patients with early stage breast cancer (BC). Intensity-modulated radiotherapy (IMRT) has the theoretical advantage of a further increase in dose conformity compared with three-dimensional techniques, with more normal tissue sparing. The aim of this randomised trial is to compare the local recurrence and survival of APBI using the IMRT technique after breast-conserving surgery to conventional whole-breast irradiation (WBI) in early stage BC. Methods This study was performed at the University of Florence (Florence, Italy). Women aged more than 40 years affected by early BC, with a maximum pathological tumour size of 25 mm, were randomly assigned in a 1:1 ratio to receive either WBI or APBI using IMRT. Patients in the APBI arm received a total dose of 30 Gy to the tumour bed in five daily fractions. The WBI arm received 50 Gy in 25 fractions, followed by a boost on the tumour bed of 10 Gy in five fractions. The primary end-point was occurrence of ipsilateral breast tumour recurrences (IBTRs); the main analysis was by intention-to-treat. This trial is registered with ClinicalTrials.gov, number NCT02104895 . Findings A total of 520 patients were randomised (260 to external WBI and 260 to APBI with IMRT) between March 2005 and June 2013. At a median follow-up of 5.0 years (Interquartile Range (IQR) 3.4–7.0), the IBTR rate was 1.5% (three cases) in the APBI group (95% confidence interval (CI) 0.1–3.0) and in the WBI group (three cases; 95% CI 0.0–2.8). No significant difference emerged between the two groups (log rank test p = 0.86). We identified seven deaths in the WBI group and only one in the APBI group ( p = 0.057). The 5-year overall survival was 96.6% for the WBI group and 99.4% for the APBI group. The APBI group presented significantly better results considering acute ( p = 0.0001), late ( p = 0.004), and cosmetic outcome ( p = 0.045). Interpretation To our knowledge, this is the first randomised study using the IMRT technique for APBI delivery. No significant difference in terms of IBTR and overall survival was observed between the two arms. APBI displayed a significantly better toxicity profile. [ABSTRACT FROM AUTHOR]

Predicting structural and energetic properties of a molecular system is one of the fundamental tasks in molecular simulations, and it has applications in chemistry, biology, and medicine. In the past decade, the advent of machine learning algorithms had an impact on molecular simulations for various tasks, including property prediction of atomistic systems. In this paper, we propose a novel methodology for transferring knowledge obtained from simple molecular systems to a more complex one, endowed with a significantly larger number of atoms and degrees of freedom. In particular, we focus on the classification of high and low free-energy conformations. Our approach relies on utilizing (i) a novel hypergraph representation of molecules, encoding all relevant information for characterizing multi-atom interactions for a given conformation, and (ii) novel message passing and pooling layers for processing and making free-energy predictions on such hypergraph-structured data. Despite the complexity of the problem, our results show a remarkable Area Under the Curve of 0.92 for transfer learning from tri-alanine to the deca-alanine system. Moreover, we show that the same transfer learning approach can also be used in an unsupervised way to group chemically related secondary structures of deca-alanine in clusters having similar free-energy values. Our study represents a proof of concept that reliable transfer learning models for molecular systems can be designed, paving the way to unexplored routes in prediction of structural and energetic properties of biologically relevant systems. Machine learning algorithms are widely employed for molecular simulations, but there are likely many yet unexplored routes for the prediction of structural and energetic properties of biologically relevant systems. Here, the authors develop a hypergraph representation and message passing method for transferring knowledge obtained from simple molecular systems onto more complex ones, demonstrated by transfer learning from tri-alanine to the deca-alanine system. [ABSTRACT FROM AUTHOR]

Research on Graph-based pattern recognition and Soft Computing systems has attracted many scientists and engineers in several different contexts. This fact is motivated by the reason that graphs are general structures able to encode both topological and semantic information in data. While the data modeling properties of graphs are of indisputable power, there are still different concerns about the best way to compute similarity functions in an effective and efficient manner. To this end, suited transformation procedures are usually conceived to address the well-known Inexact Graph Matching problem in an explicit embedding space. In this paper, we propose two graph embedding algorithms based on the Granular Computing paradigm, which are engineered as key procedures of a general-purpose graph classification system. Tests have been conducted on benchmarking datasets relying on both synthetic and real-world data, achieving competitive results in terms of test set classification accuracy. [ABSTRACT FROM AUTHOR]

In this paper, we propose a survey concerning the state of the art of the graph matching problem, conceived as the most important element in the definition of inductive inference engines in graph-based pattern recognition applications. We review both methodological and algorithmic results, focusing on inexact graph matching procedures. We consider different classes of graphs that are roughly differentiated considering the complexity of the defined labels for both vertices and edges. Emphasis will be given to the understanding of the underlying methodological aspects of each identified research branch. A selection of inexact graph matching algorithms is proposed and synthetically described, aiming at explaining some significant instances of each graph matching methodology mainly considered in the technical literature. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: To investigate the outcome of invasive early breast cancer patients that underwent breast-conserving surgery and adjuvant radiotherapy (RT), treated with a prospective margin-directed institutional policy for RT boost dose, based on final margins status (FMS). Methods and materials: A total of 2093 patients were treated between 2000 and 2008. 10Gy boost was prescribed in case of FMS>5mm; 16Gy boost with FMS between 2 and 5mm; 20Gy boost in case of FMS<2mm or positive. Results: After a median follow up of 5.2years, we recorded 41 local relapse (LR, 2%). Concerning LR free survival, age at diagnosis, nuclear grade, hormonal status, T-stage, adjuvant hormonal therapy and adjuvant chemotherapy emerged as significant parameters (p-values from log rank test <0.05). FMS, that directed the RT boost dose, did not have significant impact on LRFS (p =0.46). LR rates were 2.3% for FMS<2mm, 2.6% for 2–5mm FMS and 1.8% for FMS>5mm. At multivariate analysis, higher nuclear grade (p =0.045), triple negative subtype (p =0.036) and higher T-stage (p =0.02) resulted as the independent predictors of LR occurrence. Conclusions: Our experience showed that a margin-directed policy of RT boost dose-escalation seems to reduce the negative impact of FMS on LR, but it is not able to overcome the unfavorable effect of higher nuclear grade, higher T stage and triple negative subtype. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a rigorous way to define the concept of ambiguity in the domain of graphs. In past studies, the classical definition of ambiguity has been derived starting from fuzzy set and fuzzy information theories. Our aim is to show that also in the domain of the graphs it is possible to derive a formulation able to capture the same semantic and mathematical concept. To strengthen the theoretical results, we discuss the application of the graph ambiguity concept to the graph classification setting, conceiving a new kind of inexact graph matching procedure. The results prove that the graph ambiguity concept is a characterizing and discriminative property of graphs. [Copyright &y& Elsevier]

BACKGROUND: The objective of this study was to evaluate prognostic factors of local and distant recurrence in patients diagnosed with T1a and T1b, lymph node-negative breast carcinoma (BC) with emphasis on human epidermal growth factor receptor 2 (HER2) status. METHODS: The authors reviewed 704 women with T1aT1bN0M0 BC who received treatment at the Radiation-Oncology Center of Florence University between November 2002 and December 2008. Patients with ductal carcinoma in situ or recurrent BC at presentation and patients who received adjuvant chemotherapy were excluded from the analysis. RESULTS: In total, 75 patients had HER2-positive BC (10.7%). At a mean follow-up of 4.9 years (standard deviation, 2.6 years; range, 0.5-10.8 years), 19 events were identified, including 10 distant recurrences. Patients with HER2-positive BC had worse distant recurrence-free survival (DRFS) than patients with HER2-negative BC (hazard ratio, 3.66; 95% confidence interval, 0.94-14.69; P = .045). Negative hormone receptor (HR) status was associated significantly with worse DRFS (hazard ratio, 0.26; 95% confidence interval, 0.07-0.93; P = .026). In multivariate analysis, younger age was the only significant risk factor for an event of recurrence (hazard ratio, 0.61;95% confidence interval, 0.20-1.82; P = .029). CONCLUSIONS: The current results indicated that patients with T1a/T1b, lymph node-negative BC have a low risk of distant and local recurrence, but younger age is a significant risk factor for events occurrence. Young women with HER2-positive and HR-negative status have a significant risk of distant recurrence and should be considered for future clinical trials with anti-HER2 adjuvant therapy. Cancer 2011. © 2011 American Cancer Society. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate a retrospective single-institution outcome after hypofractionated stereotactic body radiotherapy (SBRT) for adrenal metastases. Methods and Materials: Between February 2002 and December 2009, we treated 48 patients with SBRT for adrenal metastases. The median age of the patient population was 62.7 years (range, 43–77 years). In the majority of patients, the prescription dose was 36 Gy in 3 fractions (70% isodose, 17.14 Gy per fraction at the isocenter). Eight patients were treated with single-fraction stereotactic radiosurgery and forty patients with multi-fraction stereotactic radiotherapy. Results: Overall, the series of patients was followed up for a median of 16.2 months (range, 3–63 months). At the time of analysis, 20 patients were alive and 28 patients were dead. The 1- and 2-year actuarial overall survival rates were 39.7% and 14.5%, respectively. We recorded 48 distant failures and 2 local failures, with a median interval to local failure of 4.9 months. The actuarial 1-year disease control rate was 9%; the actuarial 1- and 2-year local control rate was 90%. Conclusion: Our retrospective study indicated that SBRT for the treatment of adrenal metastases represents a safe and effective option with a control rate of 90% at 2 years. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate with a randomized clinical trial the possibility of treating the index quadrant with external intensity-modulated radiotherapy (IMRT) in a selected group of patients with early-stage breast cancer and to analyze the acute toxicity. Methods and Materials: From September 2005, a randomized Phase III clinical trial has been conducted to compare conventional (tangential field) fractionated whole breast treatment (Arm A) with accelerated partial breast irradiation plus intensity-modulated radiotherapy (Arm B). For intensity-modulated radiotherapy, the clinical target volume was drawn with a uniform 1-cm margin around the surgical clips in three dimensions. The ipsilateral and contralateral breast, ipsilateral and contralateral lung, heart, and spinal cord were contoured as organs at risk. All the regions of interest were contoured according to the International Commission on Radiation Units and Measurements reports 50 and 62 recommendations. Results: In September 2008, 259 patients were randomized and treated. The mean clinical target volume in Arm B was 44 cm3 and the mean planning target volume was 123 cm3. The mean value of the ratio between the planning target volume and the ipsilateral breast volume was 21%. The rate of Grade 1 and Grade 2 acute skin toxicity was 22% and 19% in Arm A (Radiation Therapy Oncology Group scale), respectively. The tolerance in Arm B was excellent with only 5% Grade 1 and 0.8% Grade 2 acute skin toxicity. The planning constraints were fully satisfied in most patients. In a very few cases, this was not possible because of very unfavorable anatomy. Quality assurance procedures were performed according to our internal quality assurance protocol, with excellent results. Conclusion: In the present preliminary analysis, we have demonstrated that accelerated partial breast irradiation is feasible, with very low acute toxicity. [Copyright &y& Elsevier]

The advent of effective chemo-radiotherapy has made Hodgkin Disease (HD) a highly curable malignancy, but the great improvement in survival rates allowed the observation in long-term survivors of several treatment complications. Secondary malignancies are the most serious complications and breast cancer (BC) represents the most common solid tumor among female survivors. The aim of our analysis is to describe the clinico-pathological characteristics and management of BC occurred after HD treatment. Between 1960 and 2003, 2,039 patients were treated for HD at the Department of Radiotherapy-Oncology of the Florence University. In this study we considered 1,538 patients on whom a minimum follow up of 6 months had been obtained. Of these, 725 were women. The most represented histological subtype was nodular sclerosis (50.6%). Supradiaphragmatic alone or with subdiaphragmatic complementary extended field radiotherapy was delivered to 83.1% of patients while supradiaphragmatic involved field radiotherapy was delivered to 10.7% of patients. Concerning the characteristics and incidence of BC, we focused our analysis exclusively on the female group. We found that BC occurred in 39, with an overall incidence of 5.4%. The mean interval after Hodgkin treatment was 19.5 years (SD ± 9.0). The median age of BC diagnosis was 50.8 years (SD ± 13.3) while the median age of Hodgkin diagnosis was 31.2 years (SD ± 14.5). Thirty-seven women received mediastinal irradiation. We observed a decreasing trend of the secondary BC incidence with increasing age of Hodgkin treatment with the maximum incidence registered in women treated at age 20 or younger. In Our Institute we perform a whole life follow up and recommend that annual mammography begins 10 years after HD treatment or, in any case, not later than age 40. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the outcome and predictive factors of patients who underwent breast-conserving surgery and adjuvant radiotherapy to the whole breast only, without supraclavicular nodal irradiation. Methods and Materials: A total of 5,717 patients with pT1–T4 breast cancer were treated at the University of Florence. The median age of the patient population was 55 years (range, 30–80 years). All patients were followed for a median of 6.8 years (range, 1–27 years). Adjuvant chemotherapy was recommended in 1,535 patients (26.9%). Tamoxifen was prescribed in 2,951 patients (51.6%). The patients were split into three groups according to number of positive axillary nodes (PAN): P1, negative axillary lymph nodes; P2, one to three PAN; P3, more than three PAN. Results: The P3 patients had a higher incidence of supraclavicular fossa recurrence (SFR) compared with P2 and P1 patients. However, the incidence of SFR in P3 patients was low (only 5.5%), whereas the incidence of distant metastases (DM) was 27.2%. Distant metastasis was the only independent prognostic factor for breast cancer survival. Additionally, in the subgroup of patients who developed local recurrence, DM was the most important death predictor. Conclusion: Our series suggests that isolated SFR in patients who did not receive supraclavicular radiotherapy is infrequent, as well as in those patients who have more than three PAN, and SFR seems not to influence the outcome, which depends on DM occurrence. [Copyright &y& Elsevier]

Purpose: To determine whether a boost to the tumor bed after breast-conserving surgery (BCS) and radiotherapy (RT) to the whole breast affects local control and disease-free survival. Methods and Materials: A total of 1,138 patients with pT1 to pT2 breast cancer underwent adjuvant RT at the University of Florence. We analyzed only patients with a minimum follow-up of 1 year (range, 1–20 years), with negative surgical margins. The median age of the patient population was 52.0 years (±7.9 years). The breast cancer relapse incidence probability was estimated by the Kaplan-Meier method, and differences between patient subgroups were compared by the log rank test. Cox regression models were used to evaluate the risk of breast cancer relapse. Results: On univariate survival analysis, boost to the tumor bed reduced breast cancer recurrence (p < 0.0001). Age and tamoxifen also significantly reduced breast cancer relapse (p = 0.01 and p = 0.014, respectively). On multivariate analysis, the boost and the medium age (45–60 years) were found to be inversely related to breast cancer relapse (hazard ratio [HR], 0.27; 95% confidence interval [95% CI], 0.14–0.52, and HR 0.61; 95% CI, 0.37–0.99, respectively). The effect of the boost was more evident in younger patients (HR, 0.15 and 95% CI, 0.03–0.66 for patients <45 years of age; and HR, 0.31 and 95% CI, 0.13–0.71 for patients 45–60 years) on multivariate analyses stratified by age, although it was not a significant predictor in women older than 60 years. Conclusion: Our results suggest that boost to the tumor bed reduces breast cancer relapse and is more effective in younger patients. [Copyright &y& Elsevier]

Abstract: Objectives: To review the treatment, toxicity, and outcomes in patients with Stage II seminoma after orchidectomy. Materials and methods: A retrospective chart review of all patients with Stage II seminoma referred for initial treatment, from 1965 to 2005, was performed. Treatment approaches, toxicity, and outcomes were analyzed. Results: A total of 106 patients (83 with Stage IIA, 19 with Stage IIB, and 4 with Stage IIC) were seen between 1965 and 2005. Median age at diagnosis was 36 years (range: 19–71). Median follow-up was 21 years (range: 1.2–42). Eighty-nine patients were treated with adjuvant radiotherapy alone; 13 patients received a combined treatment modality with chemotherapy and radiotherapy after orchidectomy, 4 patients were treated with chemotherapy alone. Generally the treatment was well tolerated, with the main toxicity occurring in patients treated with extended-field radiotherapy. The 5-year disease-specific survival was 96% for the entire group. The 5-year relapse-free survivals for Stages IIA, IIB, and IIC disease were 94%, 72.5%, and 75%, respectively. Fifteen patients developed a relapse and were managed by chemotherapy; 5 of them achieved complete remission and remain free from further recurrence at last follow-up, while 10 died of the disease. Second malignancies were diagnosed in 4 (3.7%) patients during the follow-up. Conclusions: In Stage IIA seminoma, radiotherapy continues to provide excellent results, as the majority of patients will be cured with this treatment alone. Radiotherapy or chemotherapy should be offered as an alternative to Stage IIB patients. Chemotherapy remains the treatment of choice for Stage IIC seminoma. [Copyright &y& Elsevier]

Purpose: To analyze the relationship between a delay in radiotherapy (RT) after breast-conserving surgery and ipsilateral breast recurrence (BR). Methods and Materials: We included in our analysis 4,820 breast cancer patients who had undergone postoperative RT at the University of Florence. The patients were categorized into four groups according to the interval between surgery and RT (T1, <60 days; T2, 61–120 days; T3, 121–180 days; and T4, >180 days). Results: On multivariate analysis, the timing of RT did not reach statistical significance in patients who received only postoperative RT (n = 1,935) or RT and hormonal therapy (HT) (n = 1,684) or RT, chemotherapy (CHT), and HT (n = 529). In the postoperative RT-only group, age at presentation, surgical margin status, and a boost to the tumor bed were independent prognostic factors for BR. In the RT plus HT group, age at presentation and boost emerged as independent prognostic factors for BR (p = 0.006 and p = 0.049, respectively). Finally, in the RT, CHT, and HT group, only multifocality was an independent BR predictor (p = 0.01). Only in the group of patients treated with RT and CHT (n = 672) did multivariate analysis with stepwise selection show RT timing as an independent prognostic factor (hazard ratio, 1.59; 95% confidence interval, 1.01–2.52; p = 0.045). Analyzing this group of patients, we found that most patients included had worse prognostic factors and had received CHT consisting of cyclophosphamide, methotrexate, and 5-fluorouracil before undergoing RT. Conclusion: The results of our study have shown that the timing of RT itself does not affect local recurrence, which is mainly related to prognostic factors. Thus, the “waiting list” should be thought of as a “programming list,” with patients scheduled for RT according to their prognostic factors. [Copyright &y& Elsevier]

Purpose: The optimal sequencing of adjuvant chemotherapy (CT) and radiation therapy (RT) in patients with early-stage breast cancer remains unclear. Patients and Methods: We retrospectively compared 485 patients treated with conservative breast surgery and postoperative whole-breast RT and six courses of CMF (cyclophosphamide 600 mg/m2, methotrexate 40 mg/m2, and 5-fluorouracil 600 mg/m2) with 300 patients who received postoperative CMF only and with 509 patients treated with postoperative whole-breast RT only. The mean radiation dose delivered was 50 Gy (range, 46–52 Gy) with standard fractionation. The boost dose was 6–16 Gy according to resection margins and at the discretion of the radiation oncologist. Acute and late RT toxicity were scored using respectively the Radiation Therapy Oncology Group and the Late Effects in Normal Tissues Subjective, Objective, Management and Analytic scale. Results: A slightly higher Grade 2 acute skin toxicity was recorded in the concurrent group (21.2% vs. 11.2% of the RT only group, p < 0.0001). RT was interrupted more frequently in the CMF/RT group respective to the RT group (8.5% vs. 4.1%; p = 0.006). There was no difference in late toxicity between the two groups. All patients in the concurrent group successfully received the planned dose of RT and CT. Local recurrence rate was 7.6% in CT/RT group and 9.8% in RT group; this difference was not statistically significant at univariate analysis (log-rank test p = 0.98). However, at multivariate analysis adjusted also for pathological tumor, pathological nodes, and age, the CT/RT group showed a statistically lower rate of local recurrence (p = 0.04). Conclusions: Whole-breast RT and concurrent CMF are a safe adjuvant treatment in terms of toxicity. [Copyright &y& Elsevier]

Abstract: Purpose: The aim of the present analysis is to determine the long-term results in terms of breast relapse and specific survival in patients treated with conserving surgery and adjuvant treatment for early breast cancer. Methods: From January 1980 to December 2001, 3834 patients with pT1-T2 breast cancer were treated consecutively at the University of Florence. The median age of the patient population was 55 years (range 30–80). All patients were followed for a median of 7.4 years (range 0.6 year to 22.5 years). The crude probability of survival (or local recurrence) was estimated by using Kaplan–Meier method, and survival (or local recurrence) comparisons were carried out using Cox proportional hazard regression models. Results: The Cox regression model by stepwise selection showed some parameters, such as chemotherapy (HR 1.53; CI 1.19–1.95), pT status (HR 1.62, CI 1.31–2.01), positive axillary lymph nodes (HR 1.92, CI 1.66–2.22), and local recurrence (HR 4.58; CI 3.66–5.73), as independent prognostic factors for breast cancer death. Moreover, we found lower rate survival among patients treated before 1991 in comparison to women treated after 1991 (p =0.0001) probably due to inadequate treatment. For local disease free survival, age at presentation (HR 0.47; CI 0.35–0.63), use of tamoxifen (HR 0.42; CI 0.25–0.71), surgical margins (HR 2.00; CI 1.21–3.30), and chemotherapy (HR 0.53; CI 0.31–0.91) emerged by multivariate analyses as significant breast relapse predictors. Conclusion: In our experience breast conserving surgery followed by adjuvant radiotherapy treatment gives high rates of local control in women with early breast cancer. The use of routinely adjuvant chemotherapy and hormone therapy lowered the local recurrence and probably the modification of therapeutic approach in the last decades also improved the specific survival. [Copyright &y& Elsevier]

The aim of this study is to determinate incidence and risk factors for loco regional failure (LRR) (breast, supraclavicular, axillary and internal mammary nodes) and indications for nodal irradiation. From January 1980 to December 2001, 4185 patients with T1–T2 breast cancer were treated with conservative surgery and whole breast radiotherapy without nodal irradiation at the University of Florence. The median age was 55 years (range 19–86). All patients were followed for a median of eight years (range 3 months to 20 years). Multivariate analysis showed as independent prognostic factors for isolated nodal relapse (NR) the presence of more than three positive lymph nodes (PAN) (p = 0.001), angiolymphatic invasion (p = 0.002) and pT2 (p = 0.02). However, only 4.8% of patients with more than three PAN developed NR as the only site of recurrence. Having one to three PAN was not associated with an increased risk of NR. We believe that it is not necessary to prescribe nodal irradiation to patients with negative or one to three PAN. Regarding patients with more than three PAN, the number of isolated NR is also small to routinely justify a node irradiation. [ABSTRACT FROM AUTHOR]

There is a significant difference in the extent of treatment offered to the elderly with breast cancer; in the United States, while 98% of patients less than 65 years of age receive standard treatment, 81% of those older than 65 years were treated according to protocol. This study's goal was to evaluate disease-specific survival and local-regional recurrence in breast cancer patients more than 65 years of age at diagnosis. A total of 1500 patients with invasive breast carcinoma were treated consecutively from May 1971 to July 2002 at the University of Florence, Florence, Italy. All patients were more than 65 years of age. The median age was 70.6 years (range 65.1–87.3 years).The median follow-up was 8.7 years (range 1–30 years). The crude probability of survival (or relapse occurrence) was estimated using the Kaplan–Meier method and survival (or relapse occurrence) comparisons were carried out using Cox proportional hazard regression models. The Cox regression model by stepwise selection showed as independent prognostic factors for disease-specific survival (DSS), the occurrence of a local relapse (p < 0.0001), pN status (p < 0.0001), the type of surgery (p < 0.0001), and the use of radiotherapy (p < 0.0006) and chemotherapy (p = 0.01). For local disease-free survival (LDFS), the Cox regression model by stepwise selection showed that mastectomy (p < 0.0001), histotype (p < 0.0001), pN status (p < 0.0001), and pT status (p = 0.001) were the only independent prognostic factors. Age was not a prognostic factor for DSS nor LDFS. We suggest treating patients with appropriate treatment for their prognostic factors. [ABSTRACT FROM AUTHOR]

Abstract: Background: We assessed the occurrence of long-bone fracture and other side effects in a group of 214 consecutive patients who underwent radical excision for soft-tissue sarcoma of the limb followed by postoperative irradiation. Methods: Two hundred fourteen patients underwent postoperative irradiation after radical excision of soft-tissue sarcoma of the limb; 156 (73%) received postoperative brachytherapy (BRT) plus external-beam radiation therapy (EBRT), and 58 (27%) underwent postoperative EBRT only. All patients were followed-up for a median time of 4.5 years (range 3 months to 10 years). Results: Seven patients developed bone fracture, which is considered severe morbidity; time between surgery and occurrence of fracture ranged between 10 and 72 months (average 31). Severe sclerosis with impairment of limb function was diagnosed in 5 and peripheral nerve damage in 3 patients. Wound complications were detected in 8 patients. Conclusions: In our series, no statistically significant correlation between bone fracture and clinical features or “technical” parameters was found, but all of the patients who experienced bone fracture (7 of 7) were postmenopausal women >55 years old. [Copyright &y& Elsevier]

Popular graph neural networks implement convolution operations on graphs based on polynomial spectral filters. In this paper, we propose a novel graph convolutional layer inspired by the auto-regressive moving average (ARMA) filter that, compared to polynomial ones, provides a more flexible frequency response, is more robust to noise, and better captures the global graph structure. We propose a graph neural network implementation of the ARMA filter with a recursive and distributed formulation, obtaining a convolutional layer that is efficient to train, localized in the node space, and can be transferred to new graphs at test time. We perform a spectral analysis to study the filtering effect of the proposed ARMA layer and report experiments on four downstream tasks: semi-supervised node classification, graph signal classification, graph classification, and graph regression. Results show that the proposed ARMA layer brings significant improvements over graph neural networks based on polynomial filters. [ABSTRACT FROM AUTHOR]

Lesions of uncertain malignant potential (B3) represent 10% of core needle biopsies (CNBs) or vacuum-assisted breast biopsies (VABBs). Traditionally, B3 lesions are operated on. This study investigated the association between B3 subtypes and malignancy to determine the best management. Pre- and postoperative histological reports from 226 patients, who had undergone excisional surgery for B3 lesions, following CNB or VABB, were retrospectively analyzed. The correlation between the CNB/VABB diagnosis and the final pathology was investigated, along with the correlation between malignancy upgrade and the type of mammographic lesion. The positive predictive value (PPV) of malignancy of B3 lesions was calculated by simple logistic regression. Patients without cancer diagnosis underwent a 7-y follow-up. Pathology showed 171 (75.6%) benign and 55 (24.3%) malignant lesions. The PPV was 24.3% (P = 0.043), including 31 (13.7%) ductal carcinomas in situ and 24 (10.6%) invasive carcinomas. The most frequently upgraded lesions were atypical ductal hyperplasia, 34.2% (P = 0.004), followed by lobular intraepithelial neoplasia, 27.5% (P = 0.025). The median diameter of mammographic lesions was 1.5 [0.9–2.5] cm, while for surgical specimens, it was 5 [4–7] cm (P < 0.0001). Mammographic findings and histology showed a significant correlation (P = 0.038). After a 7-y follow-up, 15 (8.9%) patients developed carcinoma, and 7 patients (4%) developed a new B3 lesion. We can conclude that atypical ductal hyperplasia and lobular intraepithelial neoplasia still require surgery for a significant PPV. Other types that lacked significance or confidence intervals were too wide to draw any conclusion. [ABSTRACT FROM AUTHOR]

• We design a recurrent autoencoder architecture to compress multivariate time series with missing data. • An additional regularization term aligns the learned representations with a prior kernel, which accounts for missing data. • Even with many missing data, time series belonging to different classes become well separated in the induced latent space. • We exploit the proposed architecture to design methods for anomaly detection and for imputing missing data. • We perform an analysis to investigate which kind of time series can be effectively encoded using recurrent layers. Learning compressed representations of multivariate time series (MTS) facilitates data analysis in the presence of noise and redundant information, and for a large number of variates and time steps. However, classical dimensionality reduction approaches are designed for vectorial data and cannot deal explicitly with missing values. In this work, we propose a novel autoencoder architecture based on recurrent neural networks to generate compressed representations of MTS. The proposed model can process inputs characterized by variable lengths and it is specifically designed to handle missing data. Our autoencoder learns fixed-length vectorial representations, whose pairwise similarities are aligned to a kernel function that operates in input space and that handles missing values. This allows to learn good representations, even in the presence of a significant amount of missing data. To show the effectiveness of the proposed approach, we evaluate the quality of the learned representations in several classification tasks, including those involving medical data, and we compare to other methods for dimensionality reduction. Successively, we design two frameworks based on the proposed architecture: one for imputing missing data and another for one-class classification. Finally, we analyze under what circumstances an autoencoder with recurrent layers can learn better compressed representations of MTS than feed-forward architectures. [ABSTRACT FROM AUTHOR]

Novel systemic therapies for breast cancer are being rapidly implemented into clinical practice. These drugs often have different mechanisms of action and side-effect profiles compared with traditional chemotherapy. Underpinning practice-changing clinical trials focused on the systemic therapies under investigation, thus there are sparse data available on radiotherapy. Integration of these new systemic therapies with radiotherapy is therefore challenging. Given this rapid, transformative change in breast cancer multimodal management, the multidisciplinary community must unite to ensure optimal, safe, and equitable treatment for all patients. The aim of this collaborative group of radiation, clinical, and medical oncologists, basic and translational scientists, and patient advocates was to: scope, synthesise, and summarise the literature on integrating novel drugs with radiotherapy for breast cancer; produce consensus statements on drug–radiotherapy integration, where specific evidence is lacking; and make best-practice recommendations for recording of radiotherapy data and quality assurance for subsequent studies testing novel drugs. [ABSTRACT FROM AUTHOR]

In recent years, the artificial intelligence community has seen a continuous interest in research aimed at investigating dynamical aspects of both training procedures and machine learning models. Of particular interest among recurrent neural networks, we have the Reservoir Computing (RC) paradigm characterized by conceptual simplicity and a fast training scheme. Yet, the guiding principles under which RC operates are only partially understood. In this work, we analyze the role played by Generalized Synchronization (GS) when training a RC to solve a generic task. In particular, we show how GS allows the reservoir to correctly encode the system generating the input signal into its dynamics. We also discuss necessary and sufficient conditions for the learning to be feasible in this approach. Moreover, we explore the role that ergodicity plays in this process, showing how its presence allows the learning outcome to apply to multiple input trajectories. Finally, we show that satisfaction of the GS can be measured by means of the mutual false nearest neighbors index, which makes effective to practitioners theoretical derivations. [ABSTRACT FROM AUTHOR]

Background: This study aimed to evaluate an a-priori multicriteria plan optimization algorithm (mCycle) for locally advanced breast cancer radiation therapy (RT) by comparing automatically generated VMAT (Volumetric Modulated Arc Therapy) plans (AP-VMAT) with manual clinical Helical Tomotherapy (HT) plans. Methods: The study included 25 patients who received postoperative RT using HT. The patient cohort had diverse target selections, including both left and right breast/chest wall (CW) and III-IV node, with or without internal mammary node (IMN) and Simultaneous Integrated Boost (SIB). The Planning Target Volume (PTV) was obtained by applying a 5 mm isotropic expansion to the CTV (Clinical Target Volume), with a 5 mm clip from the skin. Comparisons of dosimetric parameters and delivery/planning times were conducted. Dosimetric verification of the AP-VMAT plans was performed. Results: The study showed statistically significant improvements in AP-VMAT plans compared to HT for OARs (Organs At Risk) mean dose, except for the heart and ipsilateral lung. No significant differences in V95% were observed for PTV breast/CW and PTV III-IV, while increased coverage (higher V95%) was seen for PTV IMN in AP-VMAT plans. HT plans exhibited smaller values of PTV V105% for breast/CW and III-IV, with no differences in PTV IMN and boost. HT had an average (± standard deviation) delivery time of (17 ± 8) minutes, while AP-VMAT took (3 ± 1) minutes. The average γ passing rate for AP-VMAT plans was 97%±1%. Planning times reduced from an average of 6 h for HT to about 2 min for AP-VMAT. Conclusions: Comparing AP-VMAT plans with clinical HT plans showed similar or improved quality. The implementation of mCycle demonstrated successful automation of the planning process for VMAT treatment of locally advanced breast cancer, significantly reducing workload. [ABSTRACT FROM AUTHOR]

The rising incidence of Human Papilloma Virus (HPV) related oropharyngeal squamous cell carcinoma (OPC) in the older population has been confirmed by recent epidemiologic reports. An increase of over 50% is expected in the population aged older than 65 years in the next decade. Some authors have focused their investigations on the "late" elderly subgroup defined as patients (pts) aged 75 years or older, still underrepresented in clinical trials. Indeed, there is a significant lack of data on their disease trajectory. The purpose of our experience was to evaluate the pattern of clinical practice in this specific subgroup of pts within the Italian Association of Radiotherapy and Clinical Oncology (AIRO). [Display omitted] An observational retrospective study was conducted over a 6-year period (2015-2021). Consecutive patients older than 75 years at diagnosis with a histologically-confirmed HPV positive (p16 immunohistochemistry/HPV DNA-in situ hybridization) OPC eligible for a curatively-intended treatment were included. Overall survival (OS) was defined as the time from OPC diagnosis to last follow-up or death from any cause. Progression-free survival (PFS) was defined as the time from the last day of curative-intended treatment to disease progression or death from any cause. Median OS and PFS was estimated by the Kaplan-Meyer method. A log-rank test was employed to test different variables: smoking history, presence of caregiver, employed treatment modality and age (< or > 80 years) correlated with longer OS. Hazard ratios (HR) for the association between the variables of interest and the risk of death were obtained by univariate Cox regression analysis. A p-value <0.05 was considered statistically significant. Acute toxicity was evaluated according to CTCAE v. 5.0 [Display omitted] A cohort of 95 pts was included in our analysis. The median age was 78 years (table 1). ECOG PS 0-1 and locally advanced disease were reported for the vast majority of patients, 92.6% and 89.4% (in stage III/IV according to TNM 7thedition) respectively. As expected, exclusive radiotherapy (RT) was the most common adopted strategy. After a median follow- up of 25 months (range: 0-116), 64 patients were alive (67.3%). The one and two-year PFS were 75% and 67%, the median PFS was not reached (Figure 1a). The one and two-year OS rates were 83% and 75%, respectively, whereas the median OS was not reached. Among the tested variables, belonging to the group of age >80 years was associated with a worse OS (p=0.0429; HR for death, 2.15, 95% CI 1.00-4.60, Figure 1b), whereas no impact on survival was associated to the smoking history (p=.011), treatment modality (p=0.32) and presence of caregiver (p=0.65). The toxicity profile was acceptable (>G3 toxicity of 29.4%), although 6 patients (6.3%) died due to potential treatment-related complications. Further analyses on radiation dose, target volumes and pattern of failure will be reported To the best of our knowledge, our series represents one of the largest to date on "late" elderly population with non-metastatic HPV positive OPC treated with a curatively-intended, RT-based approach. Thanks to the appropriate selection of pts, an optimal survival outcome can be achieved with standard treatment options, in line with data reported for the younger population. Further prospective studies investigating larger series of older pts are warranted in order to confirm our conclusions. [ABSTRACT FROM AUTHOR]