Disparities in chronic spontaneous urticaria: Eligibility for drug reimbursement associated with clinical outcomes.

Background: Chronic spontaneous urticaria (CSU) is an immunologic condition with an estimated prevalence of 0.1%. For CSU that is poorly controlled despite the use of antihistamines, omalizumab is the only treatment approved and recommended by international guidelines. Objective: Our aim was to outline the impact of treatment accessibility on CSU outcomes in the real world. Methods: Serial data on adult patients with CSU receiving care for at least 6 months at a dedicated, immunologist-led urticaria clinic at Grantham Hospital in Hong Kong between 2018 and 2023 were analyzed. Patients' clinicodemographic data, drug eligibility status (eligible for reimbursement or not), treatment step, and disease activity (weekly Urticaria Activity Score [UAS7]) were collected and compared according to drug eligibility status. Results: This study included 238 patients, 80 (33.6%) of whom were eligible for reimbursement and 158 of whom were not. No significant clinicodemographic differences, including disease activity, were found at baseline. At latest follow-up, significantly more patients in the eligible group were receiving omalizumab (28.7% vs 5.7% [P < .001]), which is equivalent to a multivariate odds ratio of 9.35 (95% CI = 3.689-23.703 [P < .001]). The discrepancy persisted even in patients with moderate-to-severe CSU whose UAS7 was 16 or higher (40.6% [13 of 32] vs 10.2% [6 of 59]; P < .001). In addition, there was significantly less dose reduction (<300 mg every 4 weeks) in the eligible omalizumab users (4.3% vs 44.4% [P = .015]). Clinically, significantly greater improvements in UAS7 were reported by the eligible group (median change -8.0 vs -5.0 [P = .021]). Conclusion: Patterns of management varied largely among patients with different drug eligibility statuses and led to disparities in health outcomes. More efforts to secure equitable access to guideline-based CSU care are warranted.

Prospective validation of the role of PET/CT in detecting disease after neoadjuvant chemotherapy in advanced ovarian cancer.

OBJECTIVES: The study aimed to compare the diagnostic accuracies of 2-[18F]FDG PET/CT and contrast-enhanced CT (ceCT) after neoadjuvant chemotherapy (NACT) in advanced ovarian cancer (OC). MATERIALS AND METHODS: This study consisted historical observational cohort and prospective validation cohort. Patients with newly diagnosed stage III-IV OC scheduled for NACT were recruited, with imaging performed after three to six cycles of NACT before interval debulking surgery. Nineteen regions in the abdominopelvic cavity were scored for the presence and absence of disease, referenced to the intra-operative findings or histological specimens. Diagnostic metrics were compared using McNemar's test. RESULTS: In the historical cohort (23 patients, age 58 ± 13), 2-[18F]FDG PET had an overall accuracy (Acc) 82%, sensitivity (Sen) 38%, specificity (Spe) 97%, positive predictive value (PPV) 79% and negative predictive value (NPV) 82%; ceCT had an overall Acc 86%, Sen 64%, Spe 93%, PPV 75% and NPV 89%. In the prospective cohort (46 patients, age 59 ± 9), 2-[18F] FDG PET had an overall Acc 87%, Sen 48%, Spe 98%, PPV 84% and NPV 88%; ceCT had an overall Acc 89%, Sen 66%, Spe 95%, PPV 77% and NPV 91%. No significant difference was demonstrated between the two imaging modalities (p > 0.05). High false-negative rates were observed in the right subdiaphragmatic space, omentum, bowel mesentery and serosa. High omental metabolic uptake after NACT was associated with histological non-responders (p < 0.05). CONCLUSION: 2-[18F]FDG PET/CT had no additional value over ceCT with comparable diagnostic accuracy in detecting disease after NACT in advanced OC. CLINICAL RELEVANCE STATEMENT: 2-[18F]FDG PET/CT is not superior to contrast-enhanced CT in determining disease after neoadjuvant chemotherapy in advanced ovarian cancer; contrast-enhanced CT should be suffice for surgical planning before interval debulking surgery. KEY POINTS: • Additional value of 2-[18F]FDG PET/CT over contrast-enhanced CT is undefined in detecting disease after neoadjuvant chemotherapy. • 2-[18F]FDG PET/CT has comparable diagnostic accuracy compared to contrast-enhanced CT. • Contrast-enhanced CT will be suffice for surgical planning after neoadjuvant chemotherapy.

Clinical utility of and correlation between Sniffin' Sticks and TIB smell identification test (TIBSIT) among Hong Kong Chinese with or without chronic rhinosinusitis.

Introduction: Olfactory dysfunction (OD) is common among patients with chronic rhinosinusitis (CRS). Validated and culturally specific tests, such as the "Sniffin' Sticks" test (SST) and the TIB Smell Identification Test (TIBSIT), are crucial for the diagnosis and monitoring of OD. However, they have not been utilised in Hong Kong Chinese and their correlations are unknown. Methods: Twelve CRS patients and twenty healthy volunteers were prospectively recruited from a joint allergy-otorhinolaryngology clinic in Hong Kong and performed both SST and TIBSIT. Demographics, baseline characteristics and all test results were compared and analysed. Results: Patients with CRS demonstrated significantly lower test scores than healthy controls (all p < 0.001). Significant and strong correlations were observed between all composite and subtest scores, particularly between the composite SST and TIBSIT scores (ρ = 0.789, p < 0.001). Multivariate analysis demonstrated that the presence of CRS and increasing age were significantly associated with OD. Conclusion: Both SST and TIBSIT are useful olfactory tests and are strongly correlated among Hong Kong Chinese. We advocate that either test can be used for measuring OD among CRS patients.

Enhancing Patient-Reported Outcome Measures for Drug Hypersensitivity: A Validated 6-Item Quality-of-Life Questionnaire for Patients With Drug Hypersensitivity.

BACKGROUND: Drug hypersensitivity reactions (DHRs) can significantly impair patients' health-related quality of life (HRQoL). However, tools for HRQoL assessment for patients with DHR are time-consuming and remain underutilized. OBJECTIVE: To develop and validate an optimized version of the Drug Hypersensitivity Quality-of-Life Questionnaire (DrHy-Q) designed for everyday clinical use. METHODS: Item response theory (IRT), a statistical framework for psychometric measurement, was used to evaluate the 15 questions from the original DrHy-Q for their respective item difficulty, discrimination, and information using prospective data from 243 patients with histories of suspected/confirmed DHR before allergy workup. Accordingly, the best-performing items were identified to develop a 6-item optimized version (DrHy-Q6), which was subsequently validated with another prospective cohort of 156 patients. RESULTS: All 15 items of the original DrHy-Q demonstrated satisfactory parameters in IRT analysis, including very high discrimination (>1.7), appropriate difficulty (in between -1.5 and 1.5), and good information (a high and broad peak in the information curve). Six items with top-ranked IRT parameters were identified to construct an optimized version, which we named the DrHy-Q6. The DrHy-Q6 demonstrated a 1-factor structure with an improved fit compared with the original DrHy-Q (comparative fit index = 0.985, Tucker-Lewis index = 0.974), excellent convergent validity (unadjusted Pearson correlation with the full version = 0.955; adjusted = 0.894, P < .001), reliability (Cronbach's α and McDonald's ω = 0.93), divergent validity (Pearson correlation with all Short Form 12-item Health Survey Version 2 subscales <0.60, P < .001), and discriminant validity (significantly higher scores with multiple DHR labels [42.45 ± 27.26 vs 32.93 ± 26.66], P = .013). CONCLUSIONS: From an IRT perspective, the DrHy-Q and all its constituent items are psychometrically valid for HRQoL assessment. We propose an optimized 6-item version (DrHy-Q6) as an abbreviated alternative for assessing HRQoL in patients with DHR, especially for routine use in clinical practice. Patients and physicians may benefit from its streamlined length and simpler scoring algorithm.

PET/Computed Tomography Transformation of Oncology: Ovarian Cancers.

Over the last quarter of a century, fluorine-18-fluorodeoxyglucose (FDG) PET/computed tomography (CT) has revolutionized the diagnostic algorithm of ovarian cancer, impacting on the initial disease evaluation including staging and surgical planning, treatment response assessment and prognostication, to the most important role in detection of recurrent disease. The role of FDG PET/CT is expanding with the adoption of new therapeutic agents. Other non-FDG tracers have been explored with fibroblast activation protein inhibitor being promising. Novel tracers may provide the basis for future theragnostic work. This article will review the evolution and impact of PET/CT in ovarian cancer management.

A view of the pan-genome of domesticated Cowpea (Vigna unguiculata [L.] Walp.).

Cowpea, Vigna unguiculata L. Walp., is a diploid warm-season legume of critical importance as both food and fodder in sub-Saharan Africa. This species is also grown in Northern Africa, Europe, Latin America, North America, and East to Southeast Asia. To capture the genomic diversity of domesticates of this important legume, de novo genome assemblies were produced for representatives of six subpopulations of cultivated cowpea identified previously from genotyping of several hundred diverse accessions. In the most complete assembly (IT97K-499-35), 26,026 core and 4963 noncore genes were identified, with 35,436 pan genes when considering all seven accessions. GO terms associated with response to stress and defense response were highly enriched among the noncore genes, while core genes were enriched in terms related to transcription factor activity, and transport and metabolic processes. Over 5 million single nucleotide polymorphisms (SNPs) relative to each assembly and over 40 structural variants >1 Mb in size were identified by comparing genomes. Vu10 was the chromosome with the highest frequency of SNPs, and Vu04 had the most structural variants. Noncore genes harbor a larger proportion of potentially disruptive variants than core genes, including missense, stop gain, and frameshift mutations; this suggests that noncore genes substantially contribute to diversity within domesticated cowpea.

Design of nanoparticle-based systems for the systemic delivery of chemotherapeutics: Alternative potential routes via sublingual and buccal administration for systemic drug delivery.

Conventional therapeutic approaches for cancer generally involve chemo- and radiation therapies that often exhibit low efficacy and induce toxic side effects. Recent years have seen significant advancements in the use of protein biologics as a promising alternative treatment option. Nanotechnology-based systems have shown great potential in providing more specific and targeted cancer treatments, thus improving upon many of the limitations associated with current treatments. The unique properties of biomaterial carriers at the nanoscale have been proven to enhance both the performance of the incorporated therapeutic agent and tumor targeting; however, many of these systems are delivered intravenously, which can cause hazardous side effects. Buccal and sublingual delivery systems offer an alternative route for more efficient delivery of nanotechnologies and drug absorption into systemic circulation. This review concentrates on emerging buccal and sublingual nanoparticle delivery systems for chemo- and protein therapeutics, their development, efficacy, and potential areas of improvement in the field. Several factors contribute to the development of effective buccal or sublingual nanoparticle delivery systems, including targeting efficiency of the nanoparticulate carriers, drug release, and carrier biocompatibility. Furthermore, the potential utilization of buccal and sublingual multilayer films combined with nanoparticle chemotherapeutic systems is outlined as a future avenue for in vitro and in vivo research.

Long-term prophylaxis for hereditary angioedema: Initial experiences with garadacimab and lanadelumab.

Background: With no approved long-term prophylaxis (LTP) for the prevention of hereditary angioedema (HAE) attacks in Hong Kong, patients rely on compassionate use programs and drug trials. Moreover, studies regarding the use and efficacy of LTP in Asia are lacking. Objectives: Our aim was to assess 2 LTP medications for HAE in Hong Kong: lanadelumab and garadacimab. Methods: A prospective study was performed. Adult patients with a diagnosis of type I or type II HAE with 1 or more expert-confirmed attacks per month were consecutively recruited. The patients had been receiving treatment for at least 6 months. Clinical data were obtained, and questionnaires were administered before treatment periodically for at least 6 months following initiation of LTP. Results: Almost one-third of the patients with HAE experienced frequent attacks and began receiving LTP (8 of the 11 received garadacimab and 3 of the 11 received lanadelumab). At baseline, the time-normalized number of HAE attacks was 2.5 plus or minus 1.3 per month. At month 6, there was an overall reduction of time-normalized number of attacks per month of -2.4 attacks per month (95% CI = -3.3 to -1.5. [P < .01]). The time-normalized number of HAE attacks at month 6 was 0.1 plus or minus 0.1 per month. More than 70% of the patients (8 of 11) were completely attack-free during the 6-month period while receiving LTP, and no patients required hospitalization. LTP improved patients' scores of the Angioedema Quality-of-Life Questionnaire (P < .001) and reduced activity impairment due to health (P = .008). Patients experienced significant improvement across all dimensions of the Treatment Satisfaction for Medication Questionnaire (54.5%-76.8% [P = .002]), and no adverse events were reported. Conclusion: The patients receiving LTP with garadacimab and lanadelumab experienced a significant reduction in number of HAE attacks and improvement in quality of life, and they were satisfied with treatment.

Blackcurrant Anthocyanins Improve Blood Lipids and Biomarkers of Inflammation and Oxidative Stress in Healthy Women in Menopause Transition without Changing Body Composition.

Recent cell and animal studies suggest the potential of blackcurrants (BCs; Ribes nigrum) as a dietary agent that may reduce the risk of cardiovascular disease (CVD) by improving dyslipidemia, oxidative stress, and inflammation. This study aimed to examine the effects of BC anthocyanin (ACN) extract supplementation on biomarkers of CVD risk in healthy adult women in menopause transition. The effects of BC ACN supplementation on body composition, fasting blood lipids and biomarkers of inflammation and oxidative stress were evaluated using anthropometric measures and blood samples collected from a pilot randomized controlled clinical trial in peri- and early postmenopausal women. Thirty-eight eligible peri- and early postmenopausal women aged 45-60 completed the entire trial, in which they were randomly assigned into one of three treatment groups: placebo (control group), 392 mg/day (low BC group), or 784 mg/day (high BC group) for six months. The significance of differences in outcomes was tested using repeated-measures ANOVA. Overall, following six-month BC consumption, significantly decreased triglyceride (TG) levels were observed between treatment groups (p < 0.05) in a dose-dependent manner. Plasma interleukin-1ß (IL-1ß) was significantly reduced in a dose and time dependent manner (p < 0.05). Significant decreases in thiobarbituric acid reactive substances (TBARS) levels were also observed between treatment groups (p < 0.05) in a dose-dependent manner. Six-month change in oxidized LDL was inversely correlated with changes in catalase (CAT) and total antioxidant capacity (TAC) (p < 0.05), while C-reactive protein (hs-CRP) change was positively correlated with changes in TG and IL-1ß (p < 0.01). Together, these findings suggest that daily BC consumption for six months effectively improved dyslipidemia, inflammation, and lipid peroxidation, thus potentially mitigating the risk of postmenopausal CVD development in study participants. Future studies with larger sample sizes and at-risk populations are warranted to confirm these findings.

Plasma Proteomics-Based Discovery of Mechanistic Biomarkers of Hyperbaric Stress and Pulmonary Oxygen Toxicity.

Our aim was to identify proteins that reflect an acute systemic response to prolonged hyperbaric stress and discover potential biomarker pathways for pulmonary O2 toxicity. The study was a double-blind, randomized, crossover design in trained male Navy diver subjects. Each subject completed two dry resting hyperbaric chamber dives separated by a minimum of one week. One dive exposed the subject to 6.5 h of 100% oxygen (O2) at 2ATA. The alternate dive exposed the subjects to an enhanced air nitrox mixture (EAN) containing 30.6% O2 at the same depth for the same duration. Venous blood samples collected before (PRE) and after (POST) each dive were prepared and submitted to LC-MS/MS analysis (2 h runs). A total of 346 total proteins were detected and analyzed. A total of 12 proteins were significantly increased at EANPOST (vs. EANPRE), including proteins in hemostasis and immune signaling and activation. Significantly increased proteins at O2PRE (vs. O2POST) included neural cell adhesion molecule 1, glycoprotein Ib, catalase, hemoglobin subunit beta, fibulin-like proteins, and complement proteins. EANPOST and O2POST differed in biomarkers related to coagulation, immune signaling and activation, and metabolism. Of particular interest is (EANPOST vs. O2POST), which is protective against oxidative stress.

CT-based deep learning segmentation of ovarian cancer and the stability of the extracted radiomics features.

Background: Radiomics analysis could provide complementary tissue characterization in ovarian cancer (OC). However, OC segmentation required in radiomics analysis is time-consuming and labour-intensive. In this study, we aim to evaluate the performance of deep learning-based segmentation of OC on contrast-enhanced CT images and the stability of radiomics features extracted from the automated segmentation. Methods: Staging abdominopelvic CT images of 367 patients with OC were retrospectively recruited. The training and cross-validation sets came from center A (n=283), and testing set (n=84) came from centers B and C. The tumours were manually delineated by a board-certified radiologist. Four model architectures provided by no-new-Net (nnU-Net) method were tested in this task. The segmentation performance evaluated by Dice score, Jaccard score, sensitivity and precision were compared among 4 architectures. The Pearson correlation coefficient (ρ), concordance correlation coefficient (ρc) and Bland-Altman plots were used to evaluate the volumetric assessment of OC between manual and automated segmentations. The stability of extracted radiomics features was evaluated by intraclass correlation coefficient (ICC). Results: The 3D U-Net cascade architecture achieved highest median Dice score, Jaccard score, sensitivity and precision for OC segmentation in the testing set, 0.941, 0.890, 0.973 and 0.925, respectively. Tumour volumes of manual and automated segmentations were highly correlated (ρ=0.944 and ρc =0.933). 85.0% of radiomics features had high correlation with ICC >0.8. Conclusions: The presented deep-learning segmentation could provide highly accurate automated segmentation of OC on CT images with high stability of the extracted radiomics features, showing the potential as a batch-processing segmentation tool.

ChatGPT versus human in generating medical graduate exam multiple choice questions-A multinational prospective study (Hong Kong S.A.R., Singapore, Ireland, and the United Kingdom).

INTRODUCTION: Large language models, in particular ChatGPT, have showcased remarkable language processing capabilities. Given the substantial workload of university medical staff, this study aims to assess the quality of multiple-choice questions (MCQs) produced by ChatGPT for use in graduate medical examinations, compared to questions written by university professoriate staffs based on standard medical textbooks. METHODS: 50 MCQs were generated by ChatGPT with reference to two standard undergraduate medical textbooks (Harrison's, and Bailey & Love's). Another 50 MCQs were drafted by two university professoriate staff using the same medical textbooks. All 100 MCQ were individually numbered, randomized and sent to five independent international assessors for MCQ quality assessment using a standardized assessment score on five assessment domains, namely, appropriateness of the question, clarity and specificity, relevance, discriminative power of alternatives, and suitability for medical graduate examination. RESULTS: The total time required for ChatGPT to create the 50 questions was 20 minutes 25 seconds, while it took two human examiners a total of 211 minutes 33 seconds to draft the 50 questions. When a comparison of the mean score was made between the questions constructed by A.I. with those drafted by humans, only in the relevance domain that the A.I. was inferior to humans (A.I.: 7.56 +/- 0.94 vs human: 7.88 +/- 0.52; p = 0.04). There was no significant difference in question quality between questions drafted by A.I. versus humans, in the total assessment score as well as in other domains. Questions generated by A.I. yielded a wider range of scores, while those created by humans were consistent and within a narrower range. CONCLUSION: ChatGPT has the potential to generate comparable-quality MCQs for medical graduate examinations within a significantly shorter time.

Organophosphate Esters Disrupt Steroidogenesis in KGN Human Ovarian Granulosa Cells.

Organophosphate esters (OPEs) are used extensively as flame retardants and plasticizers and are found ubiquitously in the environment and human matrices. Previous studies suggested that exposure to some of these chemicals may disrupt the homeostasis of female sex hormones and have detrimental effects on female fertility. Here, we determined the effects of OPEs on the function of KGN ovarian granulosa cells. We hypothesized that OPEs alter the steroidogenic ability of these cells by dysregulating the expression of transcripts involved in steroid and cholesterol biosynthesis. KGN cells were exposed for 48 hours to 1 of 5 OPEs (1-50µM): triphenyl phosphate (TPHP), tris(methylphenyl) phosphate (TMPP), isopropylated triphenyl phosphate (IPPP), tert-butylphenyl diphenyl phosphate (BPDP), and tributoxyethyl phosphate (TBOEP), or to a polybrominated diphenyl ether flame retardant, 2,2',4,4' tetrabromodiphenyl ether (BDE-47), in the presence or absence of Bu2cAMP. OPEs increased the basal production of progesterone (P4) and 17ß-estradiol (E2) and had either no effect or inhibited Bu2cAMP-stimulated P4 and E2 synthesis; exposure to BDE-47 had no effect. Quantitative real-time polymerase chain reaction (qRT-PCR) analyses revealed that OPEs (≥5µM) increased the basal expression of critical genes (STAR, CYP11A1, CYP19A1, HSD3B2, and NR5A1) involved in steroidogenesis; upon stimulation, the expression of all genes tested was downregulated. An overall inhibition in cholesterol biosynthesis was induced by OPEs, characterized by a downregulation in HMGCR and SREBF2 expression. TBOEP consistently showed the least effect. Therefore, OPEs perturbed steroidogenesis in KGN granulosa cells by targeting the expression of steroidogenic enzymes and cholesterol transporters; these effects may have an adverse impact on female reproduction.

Restricted- and over-feeding during gestation decreases growth of offspring throughout maturity.

To determine the effects of poor maternal nutrition on the growth and metabolism of offspring into maturity, multiparous Dorset ewes pregnant with twins (n = 46) were fed to either 100% (control; n = 13), 60% (restricted; n = 17), or 140% (over; n = 16) of National Research Council requirements from day 30 ± 0.02 of gestation until parturition. Offspring of these ewes are referred to as CON (n = 10 ewes; 12 rams), RES (n = 13 ewes; 21 rams), or OVER (n = 16 ewes; 13 rams), respectively. Lamb body weights (BW) and blood samples were collected weekly from birth (day 0) to day 28 and then every 14 d until day 252. Intravenous glucose tolerance test (infusion of 0.25 g dextrose/kg BW) was performed at day 133 ± 0.25. At day 167 ± 1.42, individual daily intake was recorded over a 77 d feeding period to determine residual feed intake (RFI). Rams were euthanized at day 282 ± 1.82 and body morphometrics, loin eye area (LEA), back fat thickness, and organ weights were collected. The right leg was collected from rams at necropsy and dual-energy x-ray absorptiometry was used to determine bone mineral density (BMD) and length. Averaged from day 0 until day 252, RES and OVER offspring weighed 10.8% and 6.8% less than CON offspring, respectively (P ≤ 0.02). When adjusted for BW, liver and testes weights tended to be increased and decreased, respectively, in RES rams compared with CON rams (P ≤ 0.08). Additionally, RES BMD and bone length were less than CON rams (P ≤ 0.06). Treatment did not influence muscle mass, LEA, or adipose deposition (P ≥ 0.41). Rams (-0.17) were more feed efficient than ewes (0.23; P < 0.01); however, no effect of maternal diet was observed (P ≥ 0.57). At 2 min post glucose infusion, glucose concentrations in OVER offspring were greater than CON and RES offspring (P = 0.04). Concentrations of insulin in CON rams tended to be greater than OVER and RES ewes at 5 min (P ≤ 0.07). No differences were detected in insulin:glucose or area under the curve (AUC) for glucose or insulin (P ≤ 0.29). Maternal diet did not impact offspring triglycerides or cholesterol (P ≤ 0.35). Pre-weaning leptin tended to be 70% greater in OVER offspring than CON (P ≤ 0.07). These data indicate that poor maternal nutrition impairs offspring growth throughout maturity but does not affect RFI. Changes in metabolic factors and glucose tolerance are minimal, highlighting the need to investigate other mechanisms that may contribute to negative impacts of poor maternal diet.

Validation of the Chinese drug hypersensitivity quality of life questionnaire: Role of delabeling.

The Drug Hypersensitivity Quality of Life Questionnaire (DrHy-Q) is not currently available in Chinese. Besides, penicillin allergy (PA) is a worldwide public health challenge, and delabeling inauthentic PA can improve clinical and economic outcomes. However, its effect on health-related quality of life (HRQoL) remains poorly known. Objective: The study objective is to translate and validate a Chinese version of DrHy-Q and investigate the effect of PA delabeling on HRQoL using DrHy-Q. Methods: A Chinese DrHy-Q was translated then completed by patients with drug allergy labels for psychometric validation. Afterwards, another cohort of patients finished the Chinese DrHy-Q before and after their PA workup for pre-post comparison. Results: A total of 130 patients were studied. Sixty-three patients (79.4% female; median age = 59 ± 15 years) completed the Chinese DrHy-Q for validation (mean score = 38.9 ± 23.5). It demonstrated excellent internal consistency (Cronbach α = 0.956; 95% confidence interval [CI], 0.939-0.971) and test-retest reliability (intraclass correlation coefficient = 0.993 [95% CI, 0.969-0.998]). Construct validity was confirmed by its one-dimensional structure in factor analysis. Divergent validity was established because only 2 (out of 9) SF-36 scales showed weak negative correlations to DrHy-Q. Patients with multiple implicated drugs presented significantly higher DrHy-Q scores than those with only a single drug (42.0 ± 22.5 vs 28.7 ± 24.4; P = 0.038), showing discriminant validity. Subsequently, another 67 patients (73.1% female; median age = 56 ± 15 years) underwent PA investigations and completed their pre-post DrHy-Q. A significant drop in DrHy-Q score was shown (40.8 ± 21.7 vs 26.6 ± 22.5; Cohen's d = 0.964; P < 0.001), reflecting improvement in HRQoL. Conclusion: The Chinese DrHy-Q is reliable and valid for HRQoL assessment. PA delabeling significantly benefits patients' HRQoL. Future larger-scale studies are warranted to corroborate our findings.

Noninvasive imaging signatures of HER2 and HR using ADC in invasive breast cancer: repeatability, reproducibility, and association with pathological complete response to neoadjuvant chemotherapy.

BACKGROUND: The immunohistochemical test (IHC) of HER2 and HR can provide prognostic information and treatment guidance for invasive breast cancer patients. We aimed to develop noninvasive image signatures ISHER2 and ISHR of HER2 and HR, respectively. We independently evaluate their repeatability, reproducibility, and association with pathological complete response (pCR) to neoadjuvant chemotherapy. METHODS: Pre-treatment DWI, IHC receptor status HER2/HR, and pCR to neoadjuvant chemotherapy of 222 patients from the multi-institutional ACRIN 6698 trial were retrospectively collected. They were pre-separated for development, independent validation, and test-retest. 1316 image features were extracted from DWI-derived ADC maps within manual tumor segmentations. ISHER2 and ISHR were developed by RIDGE logistic regression using non-redundant and test-retest reproducible features relevant to IHC receptor status. We evaluated their association with pCR using area under receiver operating curve (AUC) and odds ratio (OR) after binarization. Their reproducibility was further evaluated using the test-retest set with intra-class coefficient of correlation (ICC). RESULTS: A 5-feature ISHER2 targeting HER2 was developed (AUC = 0.70, 95% CI 0.59 to 0.82) and validated (AUC = 0.72, 95% CI 0.58 to 0.86) with high perturbation repeatability (ICC = 0.92) and test-retest reproducibility (ICC = 0.83). ISHR was developed using 5 features with higher association with HR during development (AUC = 0.75, 95% CI 0.66 to 0.84) and validation (AUC = 0.74, 95% CI 0.61 to 0.86) and similar repeatability (ICC = 0.91) and reproducibility (ICC = 0.82). Both image signatures showed significant associations with pCR with AUC of 0.65 (95% CI 0.50 to 0.80) for ISHER2 and 0.64 (95% CI 0.50 to 0.78) for ISHER2 in the validation cohort. Patients with high ISHER2 were more likely to achieve pCR to neoadjuvant chemotherapy with validation OR of 4.73 (95% CI 1.64 to 13.65, P value = 0.006). Low ISHR patients had higher pCR with OR = 0.29 (95% CI 0.10 to 0.81, P value = 0.021). Molecular subtypes derived from the image signatures showed comparable pCR prediction values to IHC-based molecular subtypes (P value > 0.05). CONCLUSION: Robust ADC-based image signatures were developed and validated for noninvasive evaluation of IHC receptors HER2 and HR. We also confirmed their value in predicting treatment response to neoadjuvant chemotherapy. Further evaluations in treatment guidance are warranted to fully validate their potential as IHC surrogates.

A classifier-combined method for grading breast cancer based on Dempster-Shafer evidence theory.

Background: Preoperative non-invasive histologic grading of breast cancer is essential. This study aimed to explore the effectiveness of a machine learning classification method based on Dempster-Shafer (D-S) evidence theory for the histologic grading of breast cancer. Methods: A total of 489 contrast-enhanced magnetic resonance imaging (MRI) slices with breast cancer lesions (including 171 grade Ⅰ, 140 grade Ⅱ, and 178 grade Ⅲ lesions) were used for analysis. All the lesions were segmented by two radiologists in consensus. For each slice, the quantitative pharmacokinetic parameters based on a modified Tofts model and the textural features of the segmented lesion on the image were extracted. Principal component analysis was then used to reduce feature dimensionality and obtain new features from the pharmacokinetic parameters and texture features. The basic confidence assignments of different classifiers were combined using D-S evidence theory based on the accuracy of three classifiers: support vector machine (SVM), Random Forest, and k-nearest neighbor (KNN). The performance of the machine learning techniques was evaluated in terms of accuracy, sensitivity, specificity, and the area under the curve. Results: The three classifiers showed varying accuracy across different categories. The accuracy of using D-S evidence theory in combination with multiple classifiers reached 92.86%, which was higher than that of using SVM (82.76%), Random Forest (78.85%), or KNN (87.82%) individually. The average area under the curve of using the D-S evidence theory combined with multiple classifiers reached 0.896, which was larger than that of using SVM (0.829), Random Forest (0.727), or KNN (0.835) individually. Conclusions: Multiple classifiers can be effectively combined based on D-S evidence theory to improve the prediction of histologic grade in breast cancer.

Deep learning for predicting epidermal growth factor receptor mutations of non-small cell lung cancer on PET/CT images.

Background: Predicting the mutation status of the epidermal growth factor receptor (EGFR) gene based on an integrated positron emission tomography/computed tomography (PET/CT) image of non-small cell lung cancer (NSCLC) is a noninvasive, low-cost method which is valuable for targeted therapy. Although deep learning has been very successful in robotic vision, it is still challenging to predict gene mutations in PET/CT-derived studies because of the small amount of medical data and the different parameters of PET/CT devices. Methods: We used the advanced EfficientNet-V2 model to predict the EGFR mutation based on fused PET/CT images. First, we extracted 3-dimensional (3D) pulmonary nodules from PET and CT as regions of interest (ROIs). We then fused each single PET and CT image. The network model was used to predict the mutation status of lung nodules by the new data after fusion, and the model was weighted adaptively. The EfficientNet-V2 model used multiple channels to represent nodules comprehensively. Results: We trained the EfficientNet-V2 model through our PET/CT fusion algorithm using a dataset of 150 patients. The prediction accuracy of EGFR and non-EGFR mutations was 86.25% in the training dataset, and the accuracy rate was 81.92% in the validation set. Conclusions: Combined with experiments, the demonstrated PET/CT fusion algorithm outperformed radiomics methods in predicting EGFR and non-EGFR mutations in NSCLC.

A deep learning model based on the attention mechanism for automatic segmentation of abdominal muscle and fat for body composition assessment.

Background: Quantitative muscle and fat data obtained through body composition analysis are expected to be a new stable biomarker for the early and accurate prediction of treatment-related toxicity, treatment response, and prognosis in patients with lung cancer. The use of these biomarkers can enable the adjustment of individualized treatment regimens in a timely manner, which is critical to further improving patient prognosis and quality of life. We aimed to develop a deep learning model based on attention for fully automated segmentation of the abdomen from computed tomography (CT) to quantify body composition. Methods: A fully automatic segmentation deep learning model was designed based on the attention mechanism and using U-Net as the framework. Subcutaneous fat, skeletal muscle, and visceral fat were manually segmented by two experts to serve as ground truth labels. The performance of the model was evaluated using Dice similarity coefficients (DSCs) and Hausdorff distance at 95th percentile (HD95). Results: The mean DSC for subcutaneous fat and skeletal muscle were high for both the enhanced CT test set (0.93±0.06 and 0.96±0.02, respectively) and the plain CT test set (0.90±0.09 and 0.95±0.01, respectively). Nevertheless, the model did not perform well in the segmentation performance of visceral fat, especially for the enhanced CT test set. The mean DSC for the enhanced CT test set was 0.87±0.11, while the mean DSC for the plain CT test set was 0.92±0.03. We discuss the reasons for this result. Conclusions: This work demonstrates a method for the automatic outlining of subcutaneous fat, skeletal muscle, and visceral fat areas at L3.

Intersection of social determinants of symptomatic breast cancer presentation in a rural setting: A critical ethnographic study.

AIM: The aim of the study was to explore the determinants of time to presentation of women with breast cancer symptoms within a rural setting in Kenya. DESIGN: A critical ethnographic study. METHODS: Data were collected between July 2019 and April 2020 using semi-structured interviews and focus groups with 12 women and 23 disclosure recipients, respectively. Interviews and focus group discussions were audio recorded, transcribed verbatim, translated into English and thematically analysed. Further analysis using an intersectional lens added new insights into the data. Ethics approval was obtained in both Kenya and United Kingdom. RESULTS: Participants narrated their experiences from the time they self-discovered breast cancer symptoms to the time they first came into contact with a healthcare professional. The core themes identified included local cancer knowledge, embodied experience, women's responses, social networks, cultural cancer schemas, gendered social structures and healthcare system experiences. CONCLUSION: The findings revealed that symptomatic women predominantly faced multiple intersecting barriers to timely presentation. The key drivers of timeliness to presentation of women with breast cancer symptoms were identified. Several proximal and distal determinants, including economic, social, psychological and cultural determinants intersected to shape women's timeliness to symptomatic presentation. IMPACT: This study identified intersectional structural determinants to timely symptomatic presentation of women with breast cancer symptoms. The findings have global health implications for social inequalities in female breast cancer and may inform the development of intersectional interventions to promote timely symptomatic presentation. Furthermore, this study identified an additional interval, precursory interval and revision of the Model of pathway to treatment may be needed should this interval be validated by future studies. PATIENT OR PUBLIC CONTRIBUTION: To ensure the interview guides were culturally sensitive, they were co-designed with a female breast cancer survivor, nurses providing reproductive health care to women and a bilingual expert. Both women and disclosure recipients participated in scheduling for the interviews, including the mutually agreeable days and time. Participants were frequently contacted during data analysis and report writing to clarify meaning of certain words or pieces of data.