Advancing the integration of biosignal-based automated pain assessment methods into a comprehensive model for addressing cancer pain.

BACKGROUND: Tailoring effective strategies for cancer pain management requires a careful analysis of multiple factors that influence pain phenomena and, ultimately, guide the therapy. While there is a wealth of research on automatic pain assessment (APA), its integration with clinical data remains inadequately explored. This study aimed to address the potential correlations between subjective and APA-derived objectives variables in a cohort of cancer patients. METHODS: A multidimensional statistical approach was employed. Demographic, clinical, and pain-related variables were examined. Objective measures included electrodermal activity (EDA) and electrocardiogram (ECG) signals. Sensitivity analysis, multiple factorial analysis (MFA), hierarchical clustering on principal components (HCPC), and multivariable regression were used for data analysis. RESULTS: The study analyzed data from 64 cancer patients. MFA revealed correlations between pain intensity, type, Eastern Cooperative Oncology Group Performance status (ECOG), opioids, and metastases. Clustering identified three distinct patient groups based on pain characteristics, treatments, and ECOG. Multivariable regression analysis showed associations between pain intensity, ECOG, type of breakthrough cancer pain, and opioid dosages. The analyses failed to find a correlation between subjective and objective pain variables. CONCLUSIONS: The reported pain perception is unrelated to the objective variables of APA. An in-depth investigation of APA is required to understand the variables to be studied, the operational modalities, and above all, strategies for appropriate integration with data obtained from self-reporting. TRIAL REGISTRATION: This study is registered with ClinicalTrials.gov, number (NCT04726228), registered 27 January 2021, https://classic. CLINICALTRIALS: gov/ct2/show/NCT04726228?term=nct04726228&draw=2&rank=1.

Baseline Association between Healthy Eating Index-2015 and Health-Related Quality of Life in Breast Cancer Patients Enrolled in a Randomized Trial.

Health-related quality of life (HRQoL) represents one of the most concerning aspects for cancer patients. The Healthy Eating Index (HEI) is an a priori diet quality index directly associated with health outcomes and HRQoL in cancer survivors in North American populations. We evaluated, in a Mediterranean population, the baseline associations between HEI-2015 and HRQoL in 492 women with breast cancer recruited in a DEDiCa lifestyle trial. Dietary data were obtained from 7-day food records; HRQoL was assessed through the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ C30) and the C30 Summary Score (SumSc). Analysis of variance and multivariable linear and log-gamma regression models were performed. Mean and standard deviation for HEI-2015 score was 68.8 ± 11.2; SumSc was 81.5 ± 12.9. Women with lower HEI-2015 score had higher BMI, were more frequently exposed to tobacco smoke and had fewer years of education. Patients with a HEI-2015 score greater than 68.7 (median value) showed a significant increase in SumSc of 4% (p = 0.02). HEI-2015 components also associated with SumSc were beans and greens (ß = 1.04; p = 0.02). Weak associations were found for total vegetables and saturated fats. Higher diet quality in breast cancer survivors was associated with higher overall HRQoL in this cross-sectional analysis.

Central obesity, body mass index, metabolic syndrome and mortality in Mediterranean breast cancer patients.

Obesity and metabolic disorders have been associated with poor outcomes in non-Mediterranean breast cancer (BC) patients. The purpose of this study was to investigate the prognostic potential of anthropometric variables in patients with early BC living in Southern Mediterranean region of Italy. We enrolled 955 consecutive early BC patients treated in hospitals in Naples between 2009 and 2013 (median follow-up 11.8-year ending 15/09/2022). Body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and metabolic syndrome (MetS) were collected. All-cause and BC-specific mortality were calculated. At the last day of contact 208 (22%) patients had died, 131 (14%) from BC. High WC (≥ 88 cm) or WHR (> 0.85) and the MetS were significantly associated with moderately increased risk of all-cause mortality (HR=1.39, 1.62, 1.61, respectively). A significant increased risk of BC-specific mortality was found in obese patients, in those with high WC, high WHR and those with MetS (HR=1.72, 1.71, 1.80, 1.81, respectively). Central obesity significantly increased total and BC-specific mortality particularly in pre-menopausal women and in luminal subtypes, while in post-menopause MetS was a stronger risk factor. Obesity and MetS may impair the effectiveness of BC therapies hence active lifestyle interventions are encouraged.

Stereotactic body radiotherapy with CyberKnife® System for low- and intermediate-risk prostate cancer: clinical outcomes and toxicities of CyPro Trial.

Simple summary: Stereotactic body radiotherapy (SBRT) of 35-36.25 Gy in five fractions with the CyberKnife System yields excellent control with low toxicity in low-intermediate-risk prostate cancer patients. We found no differences in biochemical control and overall survival in relation to dose. There were no significant differences in toxicity or quality of life between the two groups. Aims: Stereotactic body radiotherapy (SBRT) is an emerging therapeutic approach for low- and intermediate-risk prostate cancer. We present retrospective data on biochemical control, toxicity, and quality of life of CyPro Trial. Materials and methods: A total of 122 patients with low- and intermediate-risk prostate cancer were treated with the CyberKnife System at a dose of 35 Gy or 36.25 Gy in five fractions. Biochemical failure (BF)/biochemical disease-free survival (bDFS) was defined using the Phoenix method (nadir + 2 ng/ml). Acute/late rectal and urinary toxicities were assessed by the Radiation Therapy Oncology Group (RTOG) toxicity scale. Quality of life (QoL) was assessed by the European Organisation for Research and Treatment of Cancer (EORTC) QLQ C30 and PR25. International Erectile Function Index-5 (IIEF5) and International Prostate Symptom Score (IPSS) questionnaires were administered at baseline, every 3 months after treatment during the first years, and then at 24 months and 36 months. Results: The 1-, 2-, and 5-year DFS rates were 92.9%, 92.9%, and 92.3%, respectively, while the 1-, 2-, and 5-year bDFS rates were 100%, 100%, and 95.7%, respectively. With regard to risk groups or doses, no statistically significant differences were found in terms of DFS or bDFS. Grade 2 urinary toxicity was acute in 10% and delayed in 2% of patients. No Grade 3 acute and late urinary toxicity was observed. Grade 2 rectal toxicity was acute in 8% and late in 1% of patients. No Grade 3-4 acute and late rectal toxicity was observed. Grade 2 acute toxicity appeared higher in the high-dose group (20% in the 36.25-Gy group versus 3% in the 35-Gy group) but was not statistically significant. Conclusion: Our study confirms that SBRT of 35-36.25 Gy in five fractions with the CyberKnife System produces excellent control with low toxicity in patients with low-intermediate-risk prostate cancer. We found no dose-related differences in biochemical control and overall survival. Further confirmation of these results is awaited through the prospective phase of this study, which is still ongoing.

Oligo-metastatic neoPlasms from the gastro-intestinal tract: iDentIfiCaTIon of cliNical and molecular drivers: the PREDICTION study.

BACKGROUND: Metastatic disease in tumors originating from the gastrointestinal tract can exhibit varying degrees of tumor burden at presentation. Some patients follow a less aggressive disease course, characterized by a limited number of metastatic sites, referred to as "oligo-metastatic disease" (OMD). The precise biological characteristics that define the oligometastatic behavior remain uncertain. In this study, we present a protocol designed to prospectively identify OMD, with the aim of proposing novel therapeutic approaches and monitoring strategies. METHODS: The PREDICTION study is a monocentric, prospective, observational investigation. Enrolled patients will receive standard treatment, while translational activities will involve analysis of the tumor microenvironment and genomic profiling using immunohistochemistry and next-generation sequencing, respectively. The first primary objective (descriptive) is to determine the prevalence of biological characteristics in OMD derived from gastrointestinal tract neoplasms, including high genetic concordance between primary tumors and metastases, a significant infiltration of T lymphocytes, and the absence of clonal evolution favoring specific driver genes (KRAS and PIK3CA). The second co-primary objective (analytic) is to identify a prognostic score for true OMD, with a primary focus on metastatic colorectal cancer. The score will comprise genetic concordance (> 80%), high T-lymphocyte infiltration, and the absence of clonal evolution favoring driver genes. It is hypothesized that patients with true OMD (score 3+) will have a lower rate of progression/recurrence within one year (20%) compared to those with false OMD (80%). The endpoint of the co-primary objective is the rate of recurrence/progression at one year. Considering a reasonable probability (60%) of the three factors occurring simultaneously in true OMD (score 3+), using a significance level of α = 0.05 and a test power of 90%, the study requires a minimum enrollment of 32 patients. DISCUSSION: Few studies have explored the precise genetic and biological features of OMD thus far. In clinical settings, the diagnosis of OMD is typically made retrospectively, as some patients who undergo intensive treatment for oligometastases develop polymetastatic diseases within a year, while others do not experience disease progression (true OMD). In the coming years, the identification of true OMD will allow us to employ more personalized and comprehensive strategies in cancer treatment. TRIAL REGISTRATION: ClinicalTrials.gov ID NCT05806151.

Utilizing an artificial intelligence framework (conditional generative adversarial network) to enhance telemedicine strategies for cancer pain management.

BACKGROUND: The utilization of artificial intelligence (AI) in healthcare has significant potential to revolutionize the delivery of medical services, particularly in the field of telemedicine. In this article, we investigate the capabilities of a specific deep learning model, a generative adversarial network (GAN), and explore its potential for enhancing the telemedicine approach to cancer pain management. MATERIALS AND METHODS: We implemented a structured dataset comprising demographic and clinical variables from 226 patients and 489 telemedicine visits for cancer pain management. The deep learning model, specifically a conditional GAN, was employed to generate synthetic samples that closely resemble real individuals in terms of their characteristics. Subsequently, four machine learning (ML) algorithms were used to assess the variables associated with a higher number of remote visits. RESULTS: The generated dataset exhibits a distribution comparable to the reference dataset for all considered variables, including age, number of visits, tumor type, performance status, characteristics of metastasis, opioid dosage, and type of pain. Among the algorithms tested, random forest demonstrated the highest performance in predicting a higher number of remote visits, achieving an accuracy of 0.8 on the test data. The simulations based on ML indicated that individuals who are younger than 45 years old, and those experiencing breakthrough cancer pain, may require an increased number of telemedicine-based clinical evaluations. CONCLUSION: As the advancement of healthcare processes relies on scientific evidence, AI techniques such as GANs can play a vital role in bridging knowledge gaps and accelerating the integration of telemedicine into clinical practice. Nonetheless, it is crucial to carefully address the limitations of these approaches.

[What affects diagnostic and therapeutic times for cancer patients care?] / Cosa influisce sui tempi diagnostici e terapeutici dei pazienti oncologici?

INTRODUCTION: According with "Numbers of cancer in Italy. 2021" mortality is decreasing for both the genders (-10% for men, -8% for women) in Italy. However, this trend is not uniform and seems stable in the Southern regions. Analyses of oncological care in Campania Region highlighted some structural critical issues and delays, which did not guarantee an efficient and effective use of the available economic resources. So, the Campania region established in September 2016 the Campania oncological network (Roc) addressed to prevention, diagnosis, treatment and rehabilitation of tumours through the establishment of multidisciplinary oncological groups (Gom). In February 2020, the ValPeRoc project was launched with the aim of periodically and progressively evaluating the Roc's performance both for the clinical services and for the economic aspects. METHODS: In five Goms (colon, ovary, lung, prostate, bladder) active in some Roc hospitals, the pre-Gom time elapsing between the date of diagnosis and the date of the first Gom meeting and the Gom time elapsing between the date of the first Gom meeting and the date of the treatment decision were measured. Gom times longer than 28 days were defined as high. The risk of high Gom time was analyzed with a Bart-type machine learning algorithm, considering the set of regressors (features) available to classify patients. RESULTS: The results on the test set (54 patients) report an accuracy of 0.68. The classification technique reported a good fit for colon Gom (93%) and an over-classification for lung Gom. The study of the marginal effects showed a higher risk for those who had a previous therapeutic act and for lung Gom. CONCLUSIONS: Within the Goms took in consideration the proposed statistical technique showed that, depending on each Gom, correctly classified about 70% of individuals on risk of delaying permanence within the Roc. The ValPeRoc project evaluates Roc activity for the first time through a replicable analysis of patient pathway times from diagnosis to the act of treatment. Specifically, the times analyzed measure the quality of the regional health care system.

A comparison of simplified protocols of personalized dosimetry in NEN patients treated by radioligand therapy (RLT) with [177Lu]Lu-DOTATATE to favor its use in clinical practice.

The role of internal dosimetry is usually proposed for investigational purposes in patients treated by RLT, even if its application is not yet the standard method in clinical practice. This limited use is partially justified by several concomitant factors that make calculations a complex process. Therefore, simplified dosimetry protocols are required. METHODS: In our study, dosimetric evaluations were performed in thirty patients with NENs who underwent RLT with [177Lu]Lu-DOTATATE. The reference method (M0) calculated the cumulative absorbed dose performing dosimetry after each of the four cycles. Obtained data were employed to assess the feasibility of simplified protocols: defining the dosimetry only after the first cycle (M1) and after the first and last one (M2). RESULTS: The mean differences of the cumulative absorbed doses between M1 and M0 were - 10% for kidney, - 5% for spleen, + 34% for liver, + 13% for red marrow, and + 37% for tumor lesions. Conversely, differences lower than ± 10% were measured between M2 and M0. CONCLUSION: Cumulative absorbed doses obtained with the M2 protocol resembled the doses calculated by M0, while the M1 protocol overestimated the absorbed doses in all organs at risk, except for the spleen.

A SARS-CoV-2 Infection High-Uptake Program on Healthcare Workers and Cancer Patients of the National Cancer Institute of Naples, Italy.

BACKGROUND: From the beginning of 2020, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) quickly spread worldwide, becoming the main problem for the healthcare systems. Healthcare workers (HCWs) are at higher risk of infection and can be a dangerous vehicle for the spread of the virus. Furthermore, cancer patients (CPs) are a vulnerable population, with an increased risk of developing severe and lethal forms of Coronavirus Disease 19 (COVID-19). Therefore, at the National Cancer Institute of Naples, where only cancer patients are treated, a surveillance program aimed to prevent the hospital access of SARS-CoV-2 positive subjects (HCWs and CPs) was implemented. The study aims to describe the results of the monitoring activity for the SARS-CoV-2 spread among HCWs and CPs, from March 2020 to March 2021. METHODS: This surveillance program included a periodic sampling through nasopharyngeal molecular swabs for SARS-CoV-2 (Real-Time Polymerase Chain Reaction, RT-PCR). CPs were submitted to the molecular test at least 48 h before hospital admission. Survival analysis and multiple logistic regression models were performed among HCWs and CPs to assess the main SARS-CoV-2 risk factors. RESULTS: The percentages of HCWs tested with RT-PCR for the detection of SARS-CoV-2, according to the first and the second wave, were 79.7% and 91.7%, respectively, while the percentages for the CPs were 24.6% and 39.6%. SARS-CoV-2 was detected in 20 (1.7%) HCWs of the 1204 subjects tested during the first wave, and in 127 (9.2%) of 1385 subjects tested in the second wave (p < 0.001); among CPs, the prevalence of patients tested varied from 100 (4.6%) during the first wave to 168 (4.9%) during the second wave (p = 0.8). The multivariate logistic analysis provided a significant OR for nurses (OR = 2.24, 95% CI 1.23-4.08, p < 0.001) compared to research, administrative staff, and other job titles. CONCLUSIONS: Our findings show that the positivity rate between the two waves in the HCWs increased over time but not in the CPs; therefore, the importance of adopting stringent measures to contain the shock wave of SARS-CoV-2 infection in the hospital setting was essential. Among HCWs, nurses are more exposed to contagion and patients who needed continuity in oncological care for diseases other than COVID-19, such as suspected cancer.