Organisational models supported by technology for the management of diabetic disease and its complications in a diabetic clinic setting: study protocol for a randomised controlled trial targeting type 2 diabetes individuals with non-ideal glycaemic values (Telemechron study).

INTRODUCTION: Type 2 diabetes mellitus (T2DM) is a non-communicable disease representing one of the most serious public health challenges of the twenty-first century. Its incidence continues to rise in both developed and developing countries, causing the death of 1.5 million people every year. The use of technology (e.g. smartphone application-App) in the health field has progressively increased as it has been proved to be effective in helping individuals manage their long-term diseases. Therefore, it has the potential to reduce the use of health service and its related costs. The objective of this study is to evaluate the impact of using a digital platform called "TreC Diabete" embedded into a novel organisational asset targeting poorly controlled T2DM individuals in the Autonomous Province of Trento (PAT), Italy. METHODS: This trial was designed as a multi-centre, open-label, randomised, superiority study with two parallel groups and a 1:1 allocation ratio. Individuals regularly attending outpatient diabetes clinics, providing informed consent, are randomised to be prescribed TreC Diabete platform as part of their personalised care plan. Healthcare staff members will remotely assess the data shared by the participants through the App by using a dedicated online medical dashboard. The primary end-point is the evaluation of the Hb1Ac level at 12-month post-randomisation. Data will be analysed on an intention-to-treat (ITT) basis. DISCUSSION: This trial is the first conducted in the PAT area for the use of an App specifically designed for individuals with poorly controlled T2DM. If the effects of introducing this specific App within a new organisational asset are positive, the digital platform will represent a possible way for people diagnosed with T2DM to better manage their health in the future. Results will be disseminated through conferences and peer-reviewed journals once the study is completed. TRIAL REGISTRATION: ClinicalTrials.gov NCT05629221. Registered on November 29, 2022, prior start of inclusion.

Digital Health Service for Identification of Frailty Risk Factors in Community-Dwelling Older Adults: The SUNFRAIL+ Study Protocol.

This article reports the study protocol of a nationwide multicentric study in seven Italian regions aimed at assessing the effectiveness of a digitally supported approach for the early screening of frailty risk factors in community-dwelling older adults. SUNFRAIL+ is a prospective observational cohort study aimed at carrying out a multidimensional assessment of community-dwelling older adults through an IT platform, which allows to connect the items of the SUNFRAIL frailty assessment tool with a cascading multidimensional in-depth assessment of the bio-psycho-social domains of frailty. Seven centers in seven Italian regions will administer the SUNFRAIL questionnaire to 100 older adults. According to the answers provided by older adults, they will be subjected to one or more validated in-depth scale tests in order to perform further diagnostic or dimensional evaluations. The study aims to contribute to the implementation and validation of a multiprofessional and multistakeholder service model for the screening of frailty in community-dwelling older adult population.

Supporting patients and clinicians during the breast cancer care path with AI: The Arianna solution.

The onset of cancer disease is a traumatic experience for both patients and their families that suddenly change the patient's life and is accompanied by important physical, emotional, and psycho-social problems. The complexity of this scenario has been exacerbated by the COVID-19 pandemic which dramatically affected the continuity of the provision of optimal care to chronic patients. Telemedicine can support the management of oncology care paths by furnishing a suite of effective and efficient tools to monitor the therapies of cancer patients. In particular, this is a suitable setting for therapies that are administered at home. In this paper, we present an AI-based system, called Arianna, designed and implemented to support and monitor patients treated by the professionals belonging to the Breast Cancer Unit Network (BCU-Net) along the entire clinical path of breast cancer treatment. We describe in this work the three modules composing the Arianna system (the tools for patients and clinicians, and the symbolic AI-based module). The system has been validated in a qualitative way and we demonstrated how the Arianna solution reached a high level of acceptability by all types of end-users by making it suitable for a concrete integration into the daily practice of the BCU-Net.

Food Frequency Questionnaire Personalisation Using Multi-Target Regression.

Fondazione Bruno Kessler is developing a mobile app prototype for empowering citizens to improve their health conditions through different lifestyle interventions that will be incorporated into a mobile application for lifestyle promotion of the Province of Trento in the context of the Trentino Salute 4.0 Competence Center. The envisioned interventions are based on promoting behaviour change in various domains such as physical activity, mental health and nutrition. In particular, the nutrition component is a self-monitoring module that collects dietary habits to analyse them and recommend healthier eating behaviours. Dietary assessment is completed using a Food Frequency Questionnaire on the Mediterranean diet that is presented to the user as a grid of images. The questionnaire returns feedback on 11 aspects of nutrition. Although the questionnaire used in the application only consists of 24 questions, it still could be a bit overwhelming and a bit crowded when shown on the screen. In this paper, we tried to find a machine-learning-based solution to reduce the number of questions in the questionnaire. We proposed a method that uses the user's previous answers as additional information to find the goals that need more attention. We compared this method with a case where the subset of questions is randomly selected and with a case where the subset is chosen using feature selection. We also explored how large the subset should be to obtain good predictions. All the experiments are conducted as a multi-target regression problem, which means several goals are predicted simultaneously. The proposed method adjusts well to the user in question and has the slightest error when predicting the goals.

A Remote Monitoring System to Optimize the Home Management of Oral Anticancer Therapies (ONCO-TreC): Prospective Training-Validation Trial.

BACKGROUND: A platform designed to support the home management of oral anticancer treatments and provide a secure web-based patient-health care professional communication modality, ONCO-TreC, was tested in 3 cancer centers in Italy. OBJECTIVE: The overall aims of the trial are to customize the platform; assess the system's ability to facilitate the shared management of oral anticancer therapies by patients and health professionals; and evaluate system usability and acceptability by patients, caregivers, and health care professionals. METHODS: Patients aged ≥18 years who were candidates for oral anticancer treatment as monotherapy with an Eastern Cooperative Oncology Group performance status score of 0 to 1 and a sufficient level of familiarity with mobile devices were eligible. ONCO-TreC consisted of a mobile app for patients and a web-based dashboard for health care professionals. Adherence to treatment (pill count) and toxicities reported by patients through the app were compared with those reported by physicians in medical records. Usability and acceptability were evaluated using questionnaires. RESULTS: A total of 40 patients were enrolled, 38 (95%) of whom were evaluable for adherence to treatment. The ability of the system to measure adherence to treatment was high, with a concordance of 97.3% (95% CI 86.1%-99.9%) between the investigator and system pill count. Only 60% (3/5) of grade 3, 54% (13/24) of grade 2, and 19% (7/36) of grade 1 adverse events reported by physicians in the case report forms were also reported in the app directly by patients. In total, 94% (33/35) of patients had ≥1 app launch each week, and the median number of daily accesses per patient was 2. Approximately 71% (27/38) and 68% (26/38) of patients used the app for messages and vital sign entering, respectively, at least once during the study period. CONCLUSIONS: ONCO-TreC is an important tool for measuring and monitoring adherence to oral anticancer drugs. System usability and acceptability were very high, whereas its reliability in registering toxicity could be improved. TRIAL REGISTRATION: ClinicalTrials.gov NCT02921724; https://www.clinicaltrials.gov/ct2/show/NCT02921724.

Use of the ONCO-TreC electronic diary compared with a standard paper diary to improve adherence to oral cancer therapy in patients with solid and haematological tumours: protocol for a randomised controlled trial.

INTRODUCTION: ONCO-TreC platform consists of a mobile application delivered to patients as electronic diary and a web-based dashboard managed by healthcare professionals. We aim to compare the effectiveness of ONCO-TreC electronic diary with a standard paper diary, in improving adherence to oral cancer therapy in patients with solid and haematological tumours. METHODS AND ANALYSIS: This is an open label, superiority, randomised controlled trial conducted in two Italian oncology units. Patients will be randomised with a 1:1 ratio to electronic or paper diary. For both groups a counsellor will be responsible for drug and diary delivery. The evaluation period will end after six cycles of therapy. The primary aim is to compare the proportion of non-adherent patients in the two arms. Adherence will be measured through pill count; anyone who takes less than 90% of the total prescribed drug dose will be considered non-adherent. Assuming a percentage of non-adherent patients to oral therapy of 40% in arm B, and a 60% reduction in this percentage in arm A, a sample of 124 patients will provide 80% power to identify an absolute difference greater than 24 percentage points using a bilateral Fisher's exact test with a significance level of 0.05. Considering a dropout rate of 10%, approximately 136 patients will have to be enrolled. The primary analysis will be performed on the intention-to-treat population. Secondary aims are to describe the reasons for non-adherence, the level of satisfaction of patients and healthcare professionals with the paper and electronic diary, and the impact of non-adherence in terms of healthcare costs. ETHICS AND DISSEMINATION: Ethical approval was obtained from Romagna Ethics Committee (CEROM), study ID 2108, prot. n. IRST 100.28 of 10/04/2020. Informed consent will be obtained from all study participants. Findings will be disseminated through peer-reviewed journals, conferences and event presentations. PROTOCOL VERSION: Version 2, 6 April 2021. TRIAL REGISTRATION NUMBER: NCT04826458.

Explainable AI meets persuasiveness: Translating reasoning results into behavioral change advice.

Explainable AI aims at building intelligent systems that are able to provide a clear, and human understandable, justification of their decisions. This holds for both rule-based and data-driven methods. In management of chronic diseases, the users of such systems are patients that follow strict dietary rules to manage such diseases. After receiving the input of the intake food, the system performs reasoning to understand whether the users follow an unhealthy behavior. Successively, the system has to communicate the results in a clear and effective way, that is, the output message has to persuade users to follow the right dietary rules. In this paper, we address the main challenges to build such systems: (i) the Natural Language Generation of messages that explain the reasoner inconsistency; and, (ii) the effectiveness of such messages at persuading the users. Results prove that the persuasive explanations are able to reduce the unhealthy users' behaviors.

TreC platform. An integrated and evolving care model for patients' empowerment and data repository.

INTRODUCTION: Health care has been deeply revolutionized by the new wave of information and communication technology (ICT) development, particularly related to the electronic/personal health record (PHR). The present paper describes the original design and implementation approach followed in the Trentino Province (Italy) to promote an Integrated Care Model for patients' empowerment and data repository, by means of an evolving Personal Health Record - PHR platform, named TreC (Trentino Citizens Clinical Record). MATERIALS AND METHODS: The TreC Platform is conceived as a communication hub among different stakeholders. The core assumption of the TreC platform strategy is to consider the citizen/patient as main manager and owner of both his/her own health and his/her contacts with the health care systems. RESULTS: Over the years, the TreC platform has represented the core pillar in the digitalization process promoted at Province level. This has been strategically embedded in the multi-faceted e-government strategy endorsed by the Province of Trento. So far (October 2018), more than 89,000 citizens within the Province of Trento are using TreC platform as a way to communicate with the health care system and access their own personal health records. CONCLUSIONS: The experience gained through the TreC platform implementation and its results are promising, supporting the idea that a PHR platform can represent a key driving factor in improving health care quality and efficiency, both from a patient and a health care staff perspective.

Over Expressed TKTL1, CIP-2A, and B-MYB Proteins in Uterine Cervix Epithelium Scrapings as Potential Risk Predictive Biomarkers in HR-HPV-Infected LSIL/ASCUS Patients.

High oncogenic risk human papillomaviruses (HR-HPVs) promote cervical carcinoma development, the fourth most common feminine cancer. A slow oncodevelopmental phase-defined histopathologically as Cervical Intraepithelial Neoplasia (CIN) grades 1-3, or cytologically as Low- or High-grade Squamous Intraepithelial Lesions (LSIL or HSIL)-precedes the malignancy. Cervical carcinoma screenings through HR-HPV genotyping and Pap smears are regularly performed in Western countries. Faulty cytology screening or genotyping or patients' non-compliance with follow-ups can let slip an oncoprogression diagnosis. Novel biomarker tests flanking HR-HPV genotyping and cytology could objectively predict the risk of disease progression thus helping triage LSIL/ASCUS patients. Here, anonymized leftovers of fresh cervical epithelium scrapings from twice (LSIL/ASCUS and HR-HPV DNA)-positive and twice (Pap smear- and HR-HPV DNA)-negative (control) patients in a proteome-preserving solution served to assess the biomarker worth of three cervical carcinoma-related proteins, i.e., B-MYB (or MYBL2), Cancerous Inhibitor of PP2A (CIP-2a), and transketolase-like1 (TKTL1). Leftovers anonymity was strictly kept and storage at -80°C, protein extraction, immunoblotting, and band densitometry were blindly performed. Only after tests completion, the anonymous yet code-corresponding HR-HPV-genotyping and cytology data allowed to assign each sample to the twice-positive or twice-negative group. Descriptive statistics showed that the three proteins levels significantly increased in the twice-positive vs. twice-negative scrapings. Diagnostic ROC curve analysis identified each protein's Optimal Decision Threshold (OTD) showing that TKTL1 and CIP-2a are stronger risk predictive biomarkers (Sensitivity, 0.91-0.93; Specificity, 0.77-0.83) than B-MYB. Logistic Regression coupled with Likelihood-Ratio Tests confirmed that a highly significant relation links increasing TKTL1/CIP-2a/B-MYB protein levels in twice-positive cervical scrapings to the risk of HR-HPV-driven oncoprogression. Finally, a 3 year clinical follow-up showed that 13 patients (50% of total) of the twice-positive group with biomarker values over OTDs compliantly underwent scheduled colposcopy and biopsy. Of these, 11 (i.e., 84.7%) received a positive histological diagnosis, i.e., CIN1 (n = 5; 38.5%) or CIN2/CIN2+ (n = 6; 46,2%). Therefore, TKTL1/CIP-2a/B-MYB protein levels could objectively predict oncoprogression risk in twice (HR-HPV- and Pap smear)-positive women. Further studies will assess the translatability of these findings into clinical settings.

PerKApp: A general purpose persuasion architecture for healthy lifestyles.

Automatically monitoring and supporting healthy lifestyle is a recent research trend, fostered by the availability of low-cost monitoring devices, and it can significantly contribute to the prevention of chronic diseases deriving from incorrect diet and lack of physical activity. In this paper, we present a general purpose architecture for persuasion scenarios and behavioral change. The architecture is designed to be easily portable across languages and domains and has been implemented and evaluated in a specific system for Workplace Health Promotion (WHP) called PerKApp. PerKApp provides a fully fledged platform supporting the remote monitoring of workers lifestyle by providing real-time feedback through persuasive context-based messages when necessary.

Optimisation and validation of a remote monitoring system (Onco-TreC) for home-based management of oral anticancer therapies: an Italian multicentre feasibility study.

INTRODUCTION: Despite the growing number of oral agents available for cancer treatment, their efficacy may be reduced due to the lack of adherence, inappropriate adverse event self-management and arbitrary dose adjustment. The management of anticancer therapies could exponentially benefit from the introduction of mobile health technologies in a highly integrated electronic oncology system. METHODS AND ANALYSIS: We plan to customise and fine-tune an existing monitoring TreC platform used in different chronic diseases in the oncology setting. This project follows a multistep approach with two major purposes: 1. participatory design techniques driven by Health Literacy and Patient Reported Outcomes principles in order to adapt the system to the oncology setting involving patients and healthcare providers; 2. a prospective training-validation, interventional, non-pharmacological, multicentre study on a series of consecutive patients with cancer (20 and 60 patients in the training and validation steps, respectively) in order to assess system capability, usability and acceptability. The novel Onco-TreC 2.0 is expected to contribute to improving the adherence and safety of cancer care, promoting patient empowerment and patient-doctor communication. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Independent Ethics Committees of the participating institutions (CEIIAV protocol Number 2549/2015; reference Number 1315-PU). Informed consent will be obtained from all study participants. Findings will be disseminated through peer-reviewed journals, conferences and event presentations. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov (NCT02921724); (Pre-results). Other study ID Number: IRST100.18.

Integrating mHealth in Oncology: Experience in the Province of Trento.

BACKGROUND: The potential benefits of the introduction of electronic and mobile health (mHealth) information technologies, to support the safe delivery of intravenous chemotherapy or oral anticancer therapies, could be exponential in the context of a highly integrated computerized system. OBJECTIVE: Here we describe a safe therapy mobile (STM) system for the safe delivery of intravenous chemotherapy, and a home monitoring system for monitoring and managing toxicity and improving adherence in patients receiving oral anticancer therapies at home. METHODS: The STM system is fully integrated with the electronic oncological patient record. After the prescription of chemotherapy, specific barcodes are automatically associated with the patient and each drug, and a bedside barcode reader checks the patient, nurse, infusion bag, and drug sequence in order to trace the entire administration process, which is then entered in the patient's record. The usability and acceptability of the system was investigated by means of a modified questionnaire administered to nurses. The home monitoring system consists of a mobile phone or tablet diary app, which allows patients to record their state of health, the medications taken, their side effects, and a Web dashboard that allows health professionals to check the patient data and monitor toxicity and treatment adherence. A built-in rule-based alarm module notifies health care professionals of critical conditions. Initially developed for chronic patients, the system has been subsequently customized in order to monitor home treatments with capecitabine or sunitinib in cancer patients (Onco-TreC). RESULTS: The STM system never failed to match the patient/nurse/drug sequence association correctly, and proved to be accurate and reliable in tracing and recording the entire administration process. The questionnaires revealed that the users were generally satisfied and had a positive perception of the system's usefulness and ease of use, and the quality of their working lives. The pilot studies with the home monitoring system with 43 chronic patients have shown that the approach is reliable and useful for clinicians and patients, but it is also necessary to pay attention to the expectations that mHealth solutions may raise in users. The Onco-TreC version has been successfully laboratory tested, and is now ready for validation. CONCLUSIONS: The STM and Onco-TreC systems are fully integrated with our complex and composite information system, which guarantees privacy, security, interoperability, and real-time communications between patients and health professionals. They need to be validated in order to confirm their positive contribution to the safer administration of anticancer drugs.

A mobile logbook to diagnose masked hypertension: a pilot application.

In the last years, there has been a growing interest in health mobile applications. Great benefits could be gained by seemingly "simple" solutions if these were designed to build a bridge between doctors and patients. In this paper, we describe a mobile health solution for patients allowing them to measure and record accurately their blood pressure at home, helping doctors to diagnose hypertension. An accurate measurement of the blood pressure, in fact, is a prerequisite for appropriate management of hypertension, a condition causing many serious diseases. The peculiarity of the hypertension kit is that the system requires interaction between the patients and their general practitioner. Finally, we present a pilot study carried out to evaluate the acceptability of the technologies, the compliance of patient to the self-monitoring procedure and the perceived benefits and disadvantages of both doctor and patients in using this kit.

Implementation and evaluation of an Asbru-based decision support system for adjuvant treatment in breast cancer.

The domain of cancer treatment is a promising field for the implementation and evaluation of a protocol-based clinical decision support system, because of the algorithmic nature of treatment recommendations. However, many factors can limit such systems' potential to support the decision of clinicians: technical challenges related to the interoperability with existing electronic patient records and clinical challenges related to the inherent complexity of the decisions, often collectively taken by panels of different specialists. In this paper, we evaluate the performances of an Asbru-based decision support system implementing treatment protocols for breast cancer, which accesses data from an oncological electronic patient record. Focusing on the decision on the adjuvant pharmaceutical treatment for patients affected by early invasive breast cancer, we evaluate the matching of the system's recommendations with those issued by the multidisciplinary panel held weekly in a hospital.

PI3KCA mutation status is of limited prognostic relevance in ER-positive breast cancer patients treated with hormone therapy.

PI3K/AKT/mTOR pathway alterations are frequent in patients with infiltrating breast cancer (IBC). Their clinical and pathological relevance has been insufficiently documented. We evaluated PI3KCA for mutations and the expression of PTEN, AKT, mTOR and p70S6K by immunohistochemistry in 246 IBC patients treated with hormone therapy (median follow-up, 97 months). A PI3KCA mutation was observed in 50 out of 229 informative cases (21.8 %), PTEN loss in 107 out of 210 (51 %), moderate/high level of expression of AKT in 133 out of 188 (71 %), moderate/high level of expression of mTOR in 173 out of 218 (79 %) and moderate/high level of expression of p70S6K in 111 out of 192 cases (58 %). PI3KCA mutation was associated with the absence of Her2/neu amplification/overexpression and a low level of MIB1/Ki-67 labelling. The expression of p70S6K was associated with a high level of mTOR immunoreactivity, and high PTEN expression was associated with high AKT expression level. Univariate analysis showed that PI3KCA mutation status was not associated with clinical outcome in the series as a whole or in the node-negative subgroup. However, in the node-positive subgroup, exon 9 PI3KCA mutation was associated with unfavourable overall survival (OS), although its impact on the final model in multivariate analysis seemed to be limited. Of the other markers, only high p70S6K expression was associated with a significantly prolonged OS. PI3KCA mutation status is of limited prognostic relevance in oestrogen receptor-positive breast cancer patients treated with hormone therapy.

An ontology of cancer therapies supporting interoperability and data consistency in EPRs.

Ontologies can formally describe the semantics of the medical domain in an unambiguous and machine processable form, acting as a conceptual interface between different applications that must interoperate. In this paper we present an ontology of cancer therapies originally developed to bridge the gap between an oncologic Electronic Patient Record (EPR) and a guideline-based decision support system. We show an application of the ontology complemented by rules to classify therapies recorded in the EPR. The results show how such an ontology can be used also to discover possible problems of data consistency in the EPR.

PI3KCA mutations and/or PTEN loss in Her2-positive breast carcinomas treated with trastuzumab are not related to resistance to anti-Her2 therapy.

The purpose of this study is to evaluate whether activating mutations of the p110α catalytic subunit of class A phosphoinositide 3-kinases (PI3KCA) or complete loss of phosphatase and tensin homolog (PTEN) is associated with response to anti-human epidermal growth factor receptor 2 (Her2) treatment in breast cancer (BC). We analysed PI3KCA hot-spot mutations and PTEN immunohistochemical expression in 129 Her2-positive infiltrating BC treated with trastuzumab, including 26 cases treated with neoadjuvant therapy, 48 metastatic infiltrating breast cancer (IBC; MBC) and 55 early-stage IBC, with complete clinical information (mean follow-up 37, 66 and 32 months, respectively). PI3KCA hot-spot mutations were observed in 25 cases (19 %): 12 (9 %) in exon 9 and 13 (10 %) in exon 20. No correlations were observed between mutations and pathological and biological parameters. In patients treated with neoadjuvant therapy and in MBC, we did not observe any relationship with response to trastuzumab-based therapy. PTEN loss was observed in 24 out of 86 informative cases (28 %), 3 (13 %) of which were also mutated for PI3KCA. PI3K pathway activation, defined as PI3KCA mutation and/or PTEN loss, was not associated with response to treatment or clinical outcome in MBC. PI3KCA mutation and/or PTEN loss should not exclude patients from potentially beneficial anti-Her2 therapy.

TreC - a REST-based regional PHR.

The Personal Health Record (PHR) is progressively becoming a fundamental tool to allow people to control their health. User needs, however, impose to design a PHR solution that must offer a great flexibility in terms of managing heterogeneous health data, composing data in higher level concepts and interfacing the PHR with different devices to collect and visualize data. We propose to adopt REST as core of a regional PHR architecture and present a PHR based on this architecture implemented and tested in our Province.

Diagnostic value of automated Her2 evaluation in breast cancer: a study on 272 equivocal (score 2+) Her2 immunoreactive cases using an FDA approved system.

Goal of this study was to asses the performance of Aperio computer-assisted analysis for HER2 immunohistochemical measurement in 292 equivocally (score2+) HercepTest immunoreactive breast cancer cases, evaluated by an experienced pathologist and analyzed with fluorescent in situ hybridization (FISH). The automatic Aperio categorization and the percentage of immunoreactive cells as evaluated by the computer and by the pathologist were recorded. Computer-assisted analysis classified 7 (2.4%) cases as negative (0), 136 (46.6%) as faintly positive (1+), 134 (40.5%) as moderately positive (2+), and 15 (5.1%) as strongly positive (3+). Correlative component analysis (CCA) classification is associated with Her2 amplification (P<0.0001). Compared with the human evaluation, automated CCA classification would save 157 (58%) FISH analyses, while not identifying 15 amplified cases (6% false-negative rate). The mean computer percentage value (CPV) is 18.44% standard deviation ±19.00 (range, 0.01 to 76.10). CPV and the pathologist percentage value are significantly associated and correlated (P<0.001) and have similar sensitivity and specificity in identifying Her2 FISH-amplified cases. CPV has a very low interobserver variation. The difference in CPV in amplified and nonamplified subgroups is statistically significant (P<0.001). Receiver operating characteristic analysis indicates that CPV is good at separating FISH nonamplified from amplified cases (P<0.001). The optimal cut-off value maximizing both sensitivity and specificity is 17.6% (sensitivity=73.3%, specificity=71.6%). Using a different cut-off value (2% of positive cells) we would have missed only 3 amplified cases (1% false-negative rate) while not submitting to FISH 52 cases (18% of the whole series). This false-negative rate is well below the expected false-negative rate usually observed in score 1 cases, supporting the use of CCA with a modified cut-off value in routine diagnostics for equivocally stained HER2 cases.

Embedding oncologic protocols into the provision of care: the Oncocure project.

A computerized Decision Support System (CDSS) can improve the adherence of the clinicians to clinical guidelines and protocols. Integrating it within the clinical workflow can reduce the workload of the physicians, and improve the acceptance of the system. The building of a prescriptive CDSS and its integration with a legacy cancer patient management system is the aim of the Oncocure project, which implements the existing protocol for the medical treatment of breast cancer in the Asbru language, and interfaces the Asbru interpreter with the Electronic Patient Record (EPR) in use in an oncologic unit. Our work is not constrained to a specific domain or EPR implementation, but can be generalized to other fields of medicine and patient management systems. When implemented, our CDSS is expected to reduce the cost of care while improving the adherence to the guideline and the quality of the documentation.