Patient-reported outcomes and symptom clusters pattern of chemotherapy-induced toxicity in patients with early breast cancer.

OBJECTIVE: This study aims to characterize patient-reported chemotherapy-induced toxicity in patients with breast cancer, determine its association with treatment regimens and patient characteristics, identify toxicity symptom clusters within a specific chemotherapy timeframe and analyze the correlation between symptom clusters within and between the timeframe to understand the changes and influences across chemotherapy. METHODS: Forty-six patient-reported toxicities during neoadjuvant/adjuvant chemotherapy for breast cancer were evaluated using adapted CTCAE version 4.0. Chi-Square/Fisher's Exact test was performed to analyze the difference in the incidence of toxicity symptoms by chemotherapy regimens. Poisson regression performed to assess factors associated with patient's total chemotherapy toxicity. Exploratory factor analysis (EFA) conducted to identify symptom clusters at T1 (first half) and T2 (second half of planned cycle). Factor scores were generated and Spearman correlation performed to explore the factor scores correlation between symptom clusters. RESULTS: A total of 142 patients with stage I-III breast cancer were included. The incidence of several toxicities differed significantly among three chemotherapy regimens. Subjects age ≥51 years are associated with lower number of reported toxicity (IRR/incidence rate ratio = 0.94, 95% confidence interval/CI 0.88 to 0.99, p = 0.042). Receiving more chemotherapy cycles are associated with higher number of reported toxicity (IRR = 1.06, 95% CI 1.03 to 1.10, p<0.001). Two symptom clusters identified at T1 (psychoneurological-pain/PNP-T1 and gastrointestinal-psychological/GIP-T1 cluster) and three at T2 (psychoneurological-pain/PNP-T2, epithelial/EPI-T2, and gastrointestinal cluster/GI-T2), with moderate-strong positive correlation between PNP-T1 and GIP-T2 (p<0.001), PNP-T1 and PNP-T2 (p<0.001), and GIP-T1 and PNP-T2 (p<0.001). CONCLUSIONS: This study investigated 46 patient-reported toxicities prospectively during adjuvant/neoadjuvant chemotherapy for early breast cancer. Anthracycline-taxane combination regimen had higher proportions of toxicity incidence. Subject's age and number of chemotherapy cycles significantly associated with total number of toxicity symptoms. Two symptom clusters at T1 and three at T2 were identified, with significant correlation between symptom clusters within and between chemotherapy timeframe.

Association Between Fatty Liver Index, Controlled Attenuation Parameter, and Metabolic Syndrome Stages: A Community-Based Study.

BACKGROUND Controlled attenuation parameter (CAP) is a recent ultrasound-based method for measuring hepatic steatosis, which is common in patients with metabolic syndrome (MetS). The fatty liver index (FLI), an algorithm-based method, is frequently used to evaluate hepatic steatosis. This study assessed how FLI and CAP relate to the earlier MetS stage and their ability to identify it. MATERIAL AND METHODS A total of 170 community-based individuals were studied. Demographic information, body mass index, waist circumference, and blood pressures were collected. CAP was assessed by FibroScan. Fasting glucose, lipid tests, and γ-glutamyl transferase were measured. The CAP and FLI results were categorized into quartiles, with the MetS stages as the main outcomes. The odds ratio (OR) of the outcomes was calculated using logistic regression. The area under the curve in receiver operating characteristic analysis (AUC-ROC) was used to detect the stages of MetS. Sensitivity, specificity, and appropriate cut-offs based on ROC analysis are shown. RESULTS The higher the FLI or CAP category, the lower the proportion of non-MetS and the higher the proportion of moderate MetS. Each single-quartile increase in FLI and CAP was associated with an increased likelihood of being in the higher MetS stages - FLI: adjusted OR 3.1 (2.23-4.32); CAP: adjusted OR 1.96 (1.48-2.59). In the ROC analysis, FLI had a higher AUC-ROC than CAP in separating the stages of MetS, although findings were significant (P<0.001). FLI in detecting the stages of mild-to-severe versus non-MetS performed well (AUC-ROC [95% confidence interval]: 0.79 [0.72-0.87]), with high sensitivity (0.86) but low specificity (0.62). CONCLUSIONS FLI and CAP were positively associated with the MetS stage and its components, suggesting that they could be used as a MetS screening tool in community studies.

Artificial intelligence in detecting dentomaxillofacial fractures in diagnostic imaging: a scoping review protocol.

INTRODUCTION: The dentomaxillofacial (DMF) area, which includes the teeth, maxilla, mandible, zygomaticum, orbits and midface, plays a crucial role in the maintenance of the physiological functions despite its susceptibility to fractures, which are mostly caused by mechanical trauma. As a diagnostic tool, radiographic imaging helps clinicians establish a diagnosis and determine a treatment plan; however, the presence of human factors in image interpretation can result in missed detection of fractures. Therefore, an artificial intelligence (AI) computing system with the potential to help detect abnormalities on radiographic images is currently being developed. This scoping review summarises the literature and assesses the current status of AI in DMF fracture detection in diagnostic imaging. METHODS AND ANALYSIS: This proposed scoping review will be conducted using the framework of Arksey and O'Malley, with each step incorporating the recommendations of Levac et al. By using relevant keywords based on the research questions. PubMed, Science Direct, Scopus, Cochrane Library, Springerlink, Institute of Electrical and Electronics Engineers, and ProQuest will be the databases used in this study. The included studies are published in English between 1 January 2000 and 30 June 2023. Two independent reviewers will screen titles and abstracts, followed by full-text screening and data extraction, which will comprise three components: research study characteristics, comparator and AI characteristics. ETHICS AND DISSEMINATION: This study does not require ethical approval because it analyses primary research articles. The research findings will be distributed through international conferences and peer-reviewed publications.

The occurrence and risk factors of chemotherapy-induced neutropenia in patients with breast cancer not receiving primary G-CSF prophylaxis.

Background: Chemotherapy-induced neutropenia (CIN) is a substantial side effect in chemotherapy of breast cancer patients. Administration of granulocyte colony stimulating factor (G-CSF) that may reduce CIN occurrence is not commonly available to many local cases. Objectives: To investigate the occurrence of grade 4 CIN and the influencing factors in breast cancer patients not receiving G-CSF prophylaxis. Methods: One-hundred and eighty-six newly diagnosed breast cancer patients who received a 3-weekly (neo)adjuvant or palliative chemotherapy without primary G-CSF prophylaxis were included. Grade 4 CIN was defined as absolute neutrophil count (ANC) <0.5 × 103/mm3 during any chemotherapy cycle. We used logistic regression to explore the association of clinical, pathological and treatment factors with the risk of grade 4 CIN in the first cycle and in any given cycle. Results: Fifty-seven (30.6%) patients experienced grade 4 CIN in the first cycle and 145 (78%) had it at least once during chemotherapy. In the first cycle, haemoglobin, ANC, and albumin levels were associated with grade 4 CIN (OR = 1.48, p = 0.031; OR = 0.68, p = 0.006; and OR = 2.07, p = 0.042). In any cycle, pre-treatment ANC levels and anthracycline-taxane combination regimen were associated with grade 4 CIN (OR = 0.78, p = 0.032 and OR = 3.64, p = 0.012). Conclusions: A significant proportion of the local breast cancer cases undergoing chemotherapy without primary G-CSF prophylaxis experienced grade 4 CIN. Haemoglobin, ANC, and albumin levels are the risk factors for first cycle CIN, while pre-treatment ANC levels and anthracycline-taxane chemotherapy regimen are associated with CIN in any given cycle. These risk factors may be used to direct a recommendation of G-CSF prophylaxis to the most at-risk individuals in the local setting or other settings in similar situations.

SlimMe, a Chatbot With Artificial Empathy for Personal Weight Management: System Design and Finding.

As the obesity rate continues to increase persistently, there is an urgent need to develop an effective weight loss management strategy. Nowadays, the development of artificial intelligence (AI) and cognitive technologies coupled with the rapid spread of messaging platforms and mobile technology with easier access to internet technology offers professional dietitians an opportunity to provide extensive monitoring support to their clients through a chatbot with artificial empathy. This study aimed to design a chatbot with artificial empathic motivational support for weight loss called "SlimMe" and investigate how people react to a diet bot. The SlimMe infrastructure was built using Dialogflow as the natural language processing (NLP) platform and LINE mobile messenger as the messaging platform. We proposed a text-based emotion analysis to simulate artificial empathy responses to recognize the user's emotion. A preliminary evaluation was performed to investigate the early-stage user experience after a 7-day simulation trial. The result revealed that having an artificially empathic diet bot for weight loss management is a fun and exciting experience. The use of emoticons, stickers, and GIF images makes the chatbot response more interactive. Moreover, the motivational support and persuasive messaging features enable the bot to express more empathic and engaging responses to the user. In total, there were 1,007 bot responses from 892 user input messages. Of these, 67.38% (601/1,007) of the chatbot-generated responses were accurate to a relevant user request, 21.19% (189/1,007) inaccurate responses to a relevant request, and 10.31% (92/1,007) accurate responses to an irrelevant request. Only 1.12% (10/1,007) of the chatbot does not answer. We present the design of an artificially empathic diet bot as a friendly assistant to help users estimate their calorie intake and calories burned in a more interactive and engaging way. To our knowledge, this is the first chatbot designed with artificial empathy features, and it looks very promising in promoting long-term weight management. More user interactions and further data training and validation enhancement will improve the bot's in-built knowledge base and emotional intelligence base.

Combined Effect of Inflammation and Hyperglycemia on Mild Cognitive Impairment and Associated Dietary Patterns in an Older Taiwanese Population.

BACKGROUND: Previous studies have demonstrated that C-reactive protein (CRP) and glycated hemoglobin (HbA1c) levels are independently associated with neurodegenerative diseases, which can be improved by altering dietary patterns. This study investigates the combined effect of CRP and HbA1c, as well as the influence of dietary patterns, on the risk of dementia. METHODS: A cross-sectional study was conducted with 536 participants aged ≥65 years who were recruited from the Nutrition and Health Survey in Taiwan between 2014 and 2016. The high levels of inflammation and glycation were defined as a CRP level of >0.21 mg/dl and a HbA1c level of ≥6.50%, respectively. Mild cognitive impairment (MCI) was evaluated using the Mini-Mental State Examination (MMSE) score. The dietary patterns associated with CRP and HbA1c levels were assessed using the reduced rank regression (RRR). Multivariate logistic regression analysis of both complete and imputed datasets was performed. RESULTS: Participants with high levels of both CRP and HbA1c were associated with the highest odds ratio (OR) of MCI (adjusted OR [aOR] = 3.52; 95% CI = 3.48, 3.56; p < 0.001), followed by a high level of only HbA1c (aOR = 1.73; p < 0.001) and a high level of CRP (aOR = 1.49; p < 0.001). Using the reduced rank regression, an inverse relationship between higher consumption nuts and seeds and lower levels of CRP and HbA1c was found (both factors loading < -0.2). Concerning the combined effect of tertiles among the factor 1 and factor 2 analyzed by dietary patterns, group 1 with both T3 (high tertiles) was associated with the greatest OR of MCI (aOR = 4.38; 95% CI = 4.34, 4.42; p < 0.001) using multiple imputation. CONCLUSIONS: The combined effect of high levels of inflammation and hyperglycemia was associated with an increased likelihood of MCI. Moreover, dietary patterns positively related to inflammation and hyperglycemia were associated with MCI, while eating nuts and seeds promoted better cognition.

High sensitivity C-reactive protein and glycated hemoglobin levels as dominant predictors of all-cause dementia: a nationwide population-based cohort study.

BACKGROUND: Chronic inflammation might play a major role in the pathogenesis linking diabetes mellitus (DM) to cognition. In addition, DM might be the main driver of dementia risk. The purpose of the present study was to evaluate whether inflammation, glycation, or both are associated with the risk of developing all-cause dementia (ACD). METHODS: A nationwide population-based cohort study was conducted with 4113 participants. The data were obtained from the Taiwanese Survey on Prevalence of Hypertension, Hyperglycemia, and Hyperlipidemia (TwSHHH) in 2007, which was linked with the Taiwan National Health Insurance Research Database (NHIRD). The markers of inflammation, expressed as hs-CRP, and glycation, presented as HbA1c, were measured. High levels of hs-CRP and HbA1c were defined as values greater than or equal to the 66th percentile. Developed ACD was identified based on the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. RESULTS: During 32,926.90 person-years, 106 individuals developed ACD in up to 8 years of follow-up. The study participants were separated into four categories by the top tertiles of hs-CRP and HbA1c based on the 66th percentile: high levels of both hs-CRP and HbA1c, only high levels of hs-CRP, only high levels of HbA1c, and non-high levels of hs-CRP nor HbA1c. Those who with a high level of only hs-CRP had the higher hazard for developing ACD (adjusted HR = 2.58; 95% CI = 1.29 ~ 5.17; P = 0.007), followed by the group with a high level of only HbA1c (adjusted HR = 2.52; 95% CI = 1.34 ~ 4.74; P = 0.004) and the group with high levels of both hs-CRP and HbA1c (adjusted HR = 2.36; 95% CI = 1.20 ~ 4.62; P = 0.012). Among those aged less than 65 years, hs-CRP was the only significant predictor of ACD risk (P = 0.046), whereas it did not yield any significant result in the elderly. CONCLUSIONS: A higher risk of developing ACD was found not only in patients with high levels of inflammation but also high levels of glycated hemoglobin. Future studies should focus on the clinical implementation of hs-CRP or HbA1c to monitor cognitive deficits.

Delays in the presentation and diagnosis of women with breast cancer in Yogyakarta, Indonesia: A retrospective observational study.

PURPOSE: To investigate factors associated with delays in presentation and diagnosis of women with confirmed breast cancer (BC). METHODS: A cross-sectional study nested in an ongoing prospective cohort study of breast cancer patients at Dr Sardjito Hospital, Yogyakarta, Indonesia, was employed. Participants (n = 150) from the main study were recruited, with secondary information on demographic, clinical, and tumor variables collected from the study database. A questionnaire was used to gather data on other socioeconomic variables, herbal consumption, number of healthcare visits, knowledge-attitude-practice of BC, and open-ended questions relating to initial presentation. Presentation delay (time between initial symptom and first consultation) was defined as ≥3 months. Diagnosis delay was defined as ≥1 month between presentation and diagnosis confirmation. Impact on disease stage and determinants of both delays were examined. A Kruskal-Wallis test was used to assess the length and distribution of delays by disease stage. A multivariable logistic regression analysis was conducted to explore the association between delays, cancer stage and factors. RESULTS: Sixty-five (43.3%) patients had a ≥3-month presentation delay and 97 (64.7%) had a diagnosis confirmation by ≥1 month. Both presentation and diagnosis delays increased the risk of being diagnosed with cancer stage III-IV (odds ratio/OR 2.21, 95% CI 0.97-5.01, p = 0.059 and OR 3.03, 95% CI 1.28-7.19, p = 0.012). Visit to providers ≤3 times was significantly attributed to a reduced diagnosis delay (OR 0.15, 95% CI 0.06-0.37, p <0.001), while having a family history of cancer was significantly associated with increased diagnosis delay (OR 2.28, 95% CI 1.03-5.04, p = 0.042). The most frequent reasons for delaying presentation were lack of awareness of the cause of symptoms (41.5%), low perceived severity (27.7%) and fear of surgery intervention (26.2%). CONCLUSIONS: Almost half of BC patients in our setting had a delay in presentation and 64.7% experienced a delay in diagnosis. These delays increased the likelihood of presentation with a more advanced stage of disease. Future research is required in Indonesia to explore the feasibility of evidence-based approaches to reducing delays at both levels, including educational interventions to increase awareness of BC symptoms and reducing existing complex and convoluted referral pathways for patients suspected of having cancer.

Biometric indicators can be early signs of declines in activities of daily living functioning among the Indonesian elderly.

BACKGROUND: Signs associated with the onset of disability can be useful in disability projection and have significant implications in elderly care policy. OBJECTIVE: To explored the associations between biometric screening indicators and declines in activities of daily life (ADLs) functioning among the Indonesian elderly. METHODS: This is a prospective longitudinal cohort study. The Indonesian Family Life Survey (IFLS) 4 conducted in 2007-2008, and IFLS 5 conducted in 2014-2015 were used to assess the association between biometric indicators and ADLs at baseline and follow-up. RESULTS: Findings revealed that 22.3% of participants surveyed in 2007-2014 had become disabled in terms of ADLs. Anemia status, stage 2 hypertension, lung capacity, and a longer sit-to-stand time were associated with ADLs. CONCLUSION: These findings are important to help early detection and potentially help the prevention of ADLs in elderly people in the future. Accuracy of disability estimation could possibly be improved if including biometric parameters.

Metabolic Unhealthiness Increases the Likelihood of Having Metabolic Syndrome Components in Normoweight Young Adults.

Findings on risk detection for having metabolic syndrome (MetS) components, each of which may individually increase the risk of disease and mortality, are limited in young adults. In this study, we aimed to calculate the likelihood of having ≥1 MetS component in normoweight young adults using two different metabolic health criteria. We recruited 1182 normoweight young adults from the Taiwan Survey on the Prevalence of Hypertension, Hyperglycemia, and Hyperlipidemia and the National Health Interview Survey (aged 16-45 years, 39% male, body mass index = 18.5-22.99, all without MetS) and followed them for 5 years. Metabolic health criteria were derived from the Harmonized criteria (unhealthy if showing abnormality in one or two MetS components) and the triglyceride-glucose index (TyG-i; unhealthy if TyG-i was in the >75th percentile). Odds ratio (OR) and 95% confidence interval (CI) estimations for having ≥1 MetS component and for having each MetS component in 5 years were assessed using multivariable-adjusted logistic regression. We observed a significantly increased likelihood of the presence of ≥1 MetS component in the unhealthy group by using the Harmonized criteria and TyG-i (adjusted OR (aOR); 95%CI: 2.67; 2.04-3.49 and 2.1; 1.57-2.82, respectively). The areas under the receiver-operating characteristics curves were 0.679 and 0.652 for the final models using Harmonized and TyG-i criteria, respectively. These findings support the recommendation of treating any metabolic component abnormality, even in young adults without a MetS diagnosis.