Metastatic hormone receptor-positive HR+/HER2- breast cancer represents the most common biological subtype of advanced breast cancer. Despite the significant improvements achieved with the introduction of CDK4/6 inhibitors combined with endocrine therapy, disease progression eventually occurs in a substantial proportion of patients, requiring additional therapeutic strategies. In this context, antibody-drug conjugates have emerged as one of the most relevant therapeutic innovations in recent years. We report the case of a 60-year-old woman with metastatic HR+/HER2- breast cancer with liver, nodal and bone involvement at diagnosis. The patient initially received first-line endocrine therapy with letrozole combined with abemaciclib, achieving disease control for approximately 18 months before radiological progression. She subsequently underwent chemotherapy with paclitaxel plus bevacizumab, followed by capecitabina with further progression of liver and bone metastases. Based on her treatment history and current evidence, chemotherapy with sacituzumab govitecan was initiated. Treatment is currently ongoing with radiological disease stability lasting about 10 months and good tolerability. This clinical case reflects the efficacy and manageable safety profile observed in the TROPiCS-02 trial and highlights the growing role of antibody-drug conjugates in the treatment sequence of metastatic HR+/HER2- breast cancer.
Artificial intelligence (AI) is widely regarded as one of the most promising innovations in healthcare, yet its adoption in routine clinical practice remains limited. Only a small proportion of AI applications developed in research settings are successfully integrated into healthcare delivery. Major barriers include poor interoperability with existing health information systems, complex regulatory requirements, limited scientific evidence, and the lack of clear clinical guidelines. Many AI tools have been evaluated through methodologically weak studies, often retrospective and lacking external validation, contributing to skepticism among healthcare professionals. Additional challenges involve healthcare professionals' education and training, algorithm transparency, and the ability of healthcare organizations to effectively incorporate these technologies into clinical workflows. To promote the safe and effective adoption of AI, stronger clinical evidence, structured training programs, and organizational models capable of supporting its implementation are required. Addressing these issues is essential to ensure that AI can deliver meaningful benefits for patients, healthcare professionals, and healthcare systems.
A 65-years-old woman underwent right mastectomy in 2010 for invasive ductal carcinoma of the breast (HR=95% PgR=18% ki67= 25% HER2= 0). Stage pT2(30mm)pN1(2/10)M0. She started adjuvant chemotherapy then endocrine therapy. In March 2021 a CT scan showed suspected right breast and axillary lymph node recurrence; a biopsy confirmed the luminal B, HER2- phenotype. Surgery was excluded, so she started CDK4/6 inhibitor and letrozole. One year later she started palliative radiotherapy. Because of further skin and lymph node progression, the patient began everolimus and exemestane in July 2023. The patient continued this treatment for only three months, because a new CT scan showed skin, subcutaneous and axillary lymph nodes progression. The patient started capecitabine and vinorelbine. Subsequent CT scans showed further disease progressions especially in the right axilla, leading to obstructed lymphatic drainage and consequently to upper right limb elephantiasis. Several skin nodules involving the right hemithorax were associated. The patient wore a cuff to limit oedema and started further chemotherapies, without any clinical improvement. Subsequent CT scans otherwise revealed radiological liver and bones lesions. In March 2025 she began sacituzumab govitecan (SG): after the first month, clinical examination revealed partial remission of subcutaneous nodules and pathological lymph nodes in the right axilla, gradually leading to cuff removal. The possibility to use SG in luminal breast cancer patients gave this woman a chance, in a scenario poor in exciting options.
The article presents "gut feelings" as a real component of clinical reasoning, especially in general practice, where physicians often deal with early, uncertain and vague presentations. These intuitions may appear as a sense of alarm, when something does not feel right, or as a sense of reassurance, when the situation seems likely to be benign. Gut feelings are not diagnostic magic, but signals that require critical attention. Interoception, the gut-brain axis and the emerging concept of a neurobiotic sense suggest that the body participates in decision-making, detecting discrepancies before the mind can fully explain them. Clinical intuition arises from experience, implicit memory, emotions and the doctor-patient relationship. It resembles heuristics because it supports rapid decisions under uncertainty, but it is more than a cognitive shortcut: it is an embodied perception. It should therefore be integrated with analytical reasoning, neither ignored nor treated as absolute.
The paper analyzes the concept of "Life-Sustaining Treatments" (LST) in the context of Medically Assisted Suicide (MAS) in Italy. The authors highlight how the requirement of LST, established by Constitutional Court Ruling n. 242/2019 along with three other criteria (irreversible pathology, intolerable suffering, decision-making capacity), has often been used to reject requests for access to MAS. Subsequent Constitutional Court rulings (135/2024 and 66/2025) have progressively expanded the definition of LST, including care procedures such as bowel evacuation, urinary catheterization, and mucus aspiration, and establishing that there can be no discrimination between those already undergoing treatments and those who legitimately refuse them. The authors argue that the traditional notion of LST, associated with advanced technologies such as ventilators or dialysis, is now outdated. In modern clinical practice, LST comprises the integrated set of devices, medical supplies, drugs, and care procedures that keep alive people with severe and progressive diseases, including oxygen therapy, chemotherapy, cardiovascular support medications, and nursing procedures. The document criticizes the restrictive use of the LST requirement as a "technical loophole" that prevents access to MAS, hoping that a future law will focus on essential aspects (irreversible disease, intolerable suffering, voluntariness) rather than on technological distinctions, following the example of other countries with clearer legislation on medically assisted death.
Current evaluation of artificial intelligence (AI) in healthcare remains largely focused on model accuracy, clinical outcomes, efficiency, and the formal availability of human oversight. These dimensions are necessary but insufficient. A system may improve today's decision while, through repeated use, weakening the clinician's ability to recognise tomorrow's error. Cognitive safety is proposed here as a longitudinal property of the clinician-AI-organization sociotechnical system: its capacity to support or improve clinical performance without eroding independent hypothesis generation, uncertainty calibration, reasoned dissent, metacognitive control, and resilient performance when AI is wrong or unavailable. Automation and augmentation should not be treated as ideological alternatives, but as task-sensitive regimes selected according to ambiguity, reversibility, normative content, and the need to preserve skill formation. A Clinical Cognitive Impact Assessment is outlined to make this proposal empirically testable across pre-deployment evaluation and post-implementation monitoring. Keeping a physician formally in the loop is not enough: healthcare systems must preserve over time the cognitive capacities required to understand, challenge, and, when necessary, interrupt that loop.
Riassunto. La frammentazione delle cure post-dimissione è un problema frequente per i pazienti sottoposti a interventi di chirurgia maggiore. I sistemi elettronici di supporto alle decisioni cliniche (CDSS) possono contribuire a stratificare i pazienti con artroplastica di anca e ginocchio in base a fattori clinici e sociali rilevanti, aiutando i medici a prevedere gli esiti riabilitativi, stimare i tempi di recupero e pianificare dimissioni sicure e tempestive. Per migliorare tali tecnologie, occorre verificare se rispondano alle reali priorità dei pazienti, tema oggi poco studiato. Nell'ambito del progetto di ricerca Europeo PREPARE Rehab, un team multidisciplinare sta sviluppando a) un dispositivo CDSS e b) due questionari per rilevare le aspettative di medici e pazienti. Lo scopo di questo articolo è descrivere i risultati preliminari di una sperimentazione pilota condotta su venti pazienti in riabilitazione post-artroplastica presso un ospedale ortopedico di ricerca (uno dei nove casi clinici del progetto). I risultati mostrano un certo grado di coerenza fra le risposte ottenute, confermando alcune ipotesi avanzate dalla scarsa letteratura sul tema. I risultati sono discussi alla luce dell'esperienza clinica e di ricerca, compresi i limiti di cui tenere conto nell'avanzamento dello studio. Tali risultati forniscono una base empirica per perfezionare la versione finale del questionario, e indirizzare miglioramenti ai sistemi di supporto alle decisioni cliniche prima della loro introduzione nella pratica di routine.
This paper examines the requirement of dependence on life-sustaining treatments (LSTs) for access to medical assistance in dying (MAID) - in the form of medically assisted suicide under Italian law - introduced by Constitutional Court Judgment No. 242/2019 and subsequently reaffirmed. Considered in relation to the requirement that patients be capable of making free and informed decisions, this criterion may give rise to paradoxes. The condition of being a "trapped body", often associated with dependence on LSTs, may make it more difficult to distinguish a stable wish to die from a depressive response related to the burden of such a condition, than in individuals with greater functional autonomy. Interpreting the LST requirement as evidence of highly complex clinical care does not resolve some remaining issues: the multidimensional needs of patients with incurable illnesses suggest that dependence on LSTs alone cannot be regarded as sufficient evidence of adequate care, as unmet needs capable of contributing to a request for MAID may persist. The paper therefore argues for a case-by-case assessment that responds to the actual and present suffering of the individuals concerned.
The case concerns a 68-year-old female patient with metastatic HR-positive/HER2-negative pleomorphic lobular breast carcinoma and severe chronic renal impairment since diagnosis, previously treated with multiple lines of therapy. At diagnosis in September 2021, the disease was already metastatic, with bone, nodal, and pleural involvement. The patient received endocrine therapy with CDK4/6 inhibitors, chemotherapy, and targeted agents, with subsequent multiorgan progression. The clinical course was further complicated by persistent severe renal impairment requiring urinary diversion procedures prior to sacituzumab govitecan initiation. In November 2025, the patient experienced multiorgan progression and clinical deterioration (ECOG PS 2), including ascites, peripheral edema, dyspnea, and anorexia. Following multidisciplinary evaluation, sacituzumab govitecan was initiated in December 2025 at full dose (10 mg/kg), with primary prophylaxis using filgrastim. During the first cycle, worsening renal function and grade 2 toxicity occurred, leading to omission of day 8 administration. Treatment was subsequently resumed at a reduced dose (7.5 mg/kg), achieving good tolerability, stabilization of renal function, and clinical benefit. At reassessment in March 2026, a partial response was documented. The patient is currently continuing treatment with overall good tolerability. This case highlights the feasibility of a personalized approach with sacituzumab govitecan in frail patients with severe renal impairment and lobular breast cancer, populations underrepresented in clinical trials.
Il carcinoma mammario metastatico HR+/HER2- rappresenta la forma biologica più frequente di neoplasia mammaria avanzata. Nonostante i significativi progressi ottenuti con l’introduzione degli inibitori di CDK4/6 associati alla terapia endocrina, la progressione di malattia rimane inevitabile per una quota rilevante di pazienti, rendendo necessario il ricorso a ulteriori strategie terapeutiche. In questo contesto, gli anticorpi farmaco coniugati rappresentano una delle innovazioni più rilevanti degli ultimi anni. Si descrive il caso di una donna di 60 anni con carcinoma mammario metastatico HR+/HER2- a livello epatico, linfonodale e scheletrico alla diagnosi. Dopo un iniziale trattamento con letrozolo e abemaciclib, ottenendo un controllo di malattia per circa 18 mesi, la paziente ha presentato progressione radiologica. Successivamente ha ricevuto chemioterapia con paclitaxel in associazione a bevacizumab, seguita da capecitabina con successiva progressione epatica e ossea. In considerazione della storia terapeutica e delle evidenze disponibili in letteratura, è stata avviata terapia con sacituzumab govitecan. Il trattamento è attualmente in corso con stabilità di malattia documentata da circa 10 mesi e buona tollerabilità clinica. Il caso conferma, nella pratica clinica reale, l’efficacia e la gestibilità del farmaco osservate nello studio TROPiCS-02 e sottolinea il ruolo crescente degli anticorpi farmaco coniugati nella sequenza terapeutica del carcinoma mammario HR+/HER2- metastatico.
This national cross-sectional survey (n=287) explored the adoption of Artificial Intelligence (AI) and telemedicine among Italian primary care physicians. Despite near-universal digital awareness (92.3%), structural telemedicine use remains limited (26.5%), while generative AI (ChatGPT) has been spontaneously adopted by 51.2% of respondents, primarily to manage administrative burden. Binary logistic regression identified younger age and active scientific engagement as independent predictors of ChatGPT adoption. These findings suggest that the spontaneous adoption of generative AI currently outpaces institutional governance, highlighting the need for targeted training and GDPR-compliant infrastructures within the DM77/2022 reform framework.
