Inform Treatment Decisions Research Articles

Abstract A014: Effects of senescence on the lung tumor microenvironment

Abstract Despite progress in screening and treatment, lung cancer remains the leading cause of cancer- related deaths worldwide. An overarching issue is the complexity and heterogeneous nature of the tumor microenvironment and eventual tumor spread. While aging is a key determinant, the relationship between aging and cancer is multi-faceted and extends beyond the accumulation of mutations. Therefore, a much-needed framework integrating the mechanistic principles that change with aging to drive neoplastic transformation beyond genetics will help us uncover predictive biomarkers that inform treatment decision-making and how we may use them to prevent, postpone, suppress tumor growth, and limit spread. Here, we investigate the role of age-related senescent cell accumulation in lung tumorigenesis and propose a potential strategy to delay tumor progression and spread by selectively targeting tumor-promoting senescent cells that arise with increasing age to sustain protective antitumor immunity. Citation Format: Luis Prieto. Effects of senescence on the lung tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr A014.

Upadacitinib Versus Filgotinib in Ulcerative Colitis: Is the Evidence Sufficient to Inform Treatment Decisions?

Upadacitinib Versus Filgotinib in Ulcerative Colitis: Is the Evidence Sufficient to Inform Treatment Decisions?

Abstract 4135852: Safety and Post-operative Complications of Endovascular Versus Surgical Versus Follow-up and Medical Treatment for Patients with Vertebrobasilar Artery Stenosis: Propensity Score Weighting and a Machine Learning Driven Analysis

Background: Vertebrobasilar artery stenosis (VBAS) can cause posterior circulation strokes (PCS). Optimal management is controversial, with options including medical therapy (MT), endovascular stenting (ES), and surgical revascularization (SR). This study compares outcomes of these treatments and evaluates the correlation between clinical features and medical history with 30-day outcome. Methods: Patients with VBAS were identified from the 2017-2018 National Inpatient Sample (NIS). Propensity scores adjusted for baseline differences. Outcomes included mortality, neurological complications (NC), discharge destination (DD), length of stay (LOS), total charges (TC), and procedural complications (PC). Predictive ability of clinical variables was assessed using logistic regression (LR) and machine learning techniques (MLT). Results: Of 1,343 patients, 1,061 (79.0%) received NI, 234 (17.4%) underwent ES, and 24 (1.8%) had SR. Mean age was 69.45 years, with 64.1% male. Demographics: 69.8% White, 14.9% Black, 10.0% Hispanic, and 5.3% other races. Hypertension (HTN, 85.4%) and diabetes (DM, 18.9%) were prevalent. After propensity weighting, ES was associated with higher odds of mortality, surgical/medical complications (SMC), and device/graft complications (DGC) compared to NI. SR showed a non-significant trend toward higher non-home discharges (NHD). ES and SR groups had higher resource utilization with longer LOS and greater TC. Clinical variables alone were weak predictors, with AUC values ranging from 0.454 to 0.71 across different outcomes and models. Conclusion: ES of VBAS was associated with higher mortality and complication rates compared to MT alone, with inconsistent benefits for NC. SR also carried elevated risks without clear advantages over MT. These results support that current clinical independent variables from the NIS are weak predictors. This highlights the limitation of the database in relying solely on clinical and medical history, and suggests that future use of radiological and anatomical features can improve predictions of outcomes and determination of subgroups that can benefit from certain treatment. More studies should be conducted, including post hoc analyses based on radiological and anatomical features, to better inform treatment decisions and determine subgroups that can benefit from intervention or surgery. These findings suggest a need for judicious patient selection and reinforce the role of optimal MT.

Gene-eral survey to describe genomic education needs in hospital pharmacy departments in the West Midlands and Oxford

Abstract Introduction Genomic medicine is a rapidly developing field and a priority for the NHS to ensure it is embedded into Medicine Service Alliance is that the NHS staff have understanding and confidence to utilise genomics safely and effectively. Pharmacy professionals, as experts in medicines, will lead the implementation and delivery of pharmacogenomics and wider genomic medicine services across all healthcare sectors1. Aim To understand current levels of genomic education across NHS Trust Pharmacy Departments in the Central and South region, and preferences for types of future learning. Methods A MS Forms survey was distributed across the Pharmacy Departments of five NHS Trusts, emailed to all local pharmacy staff via the Education and Training lead pharmacists; all pharmacy staff were eligible to participate, and total numbers of staff were not available. The survey was based on a previously published national survey2, but reduced in content to allow completion within 5 minutes; content was agreed between the genomics specialist pharmacy team at C&S. Ethics approval was not sought as this baseline evaluation formed part of a planned service improvement. Results One hundred and twenty-nine respondents participated in the survey, including pharmacists (62%), pharmacy technicians (29%) and assistant technical officers (5%). Seventy-one out of 127 respondents (56%) had more than 10 years of experience since qualified. Given a scale of ’very low-low-medium -high-very high’, the majority of the 127 respondents (63%) considered their knowledge about Genomic Medicine to be medium or high, and no responder considered themselves to have a very high level of knowledge about Genomic Medicine. Most participants saw the relevance of Genomic Medicine to their professions, particularly in areas like personalised medicine and 82% expressed an interest in learning more about Genomic Medicine and 15% answered ’Maybe’; the cohort had a preference for in-person meetings and seminars (32%), followed by on-line meetings (27%). Discussion / Conclusion Respondents saw the relevance of Genomic Medicine to their professions, and showed a mixture of enthusiasm, curiosity, and uncertainty about Genomic Medicine, with no respondent feeling they had a very high level of knowledge of Genomic Medicine. Most pharmacy staff in the 5 departments surveyed have an interest in furthering their knowledge of Genomic Medicine, with a marked preference for in-person meetings and seminars. Respondents recognised the potential benefits such as personalized medicine, improved treatment outcomes and reduced trial-and-error approaches in medication selection, with expectations that Genomic Medicine will improve patient care and outcomes, reducing adverse events and informing treatment decisions Limitations to this study include an inability to judge response rate due to lack of denominator data, however relatively similar numbers were obtained from each Department, with a good mix of respondent roles. An in-person training event with hybrid online options is being planned as a result of this work.

Comparing five-year and ten-year predicted cardiovascular disease risk in Aotearoa New Zealand: national data linkage study of 1.7 million adults.

There is no consensus on the optimal time horizon for predicting cardiovascular disease (CVD) risk to inform treatment decisions. New Zealand and Australia recommend 5 years, whereas most countries recommend 10 years. We compared predicted risk and treatment-eligible groups using 5-year and 10-year equations. Individual-level linked administrative datasets identified 1,746,665 New Zealanders without CVD, aged 30-74 years in 2006, with follow-up to 2018. Participants were randomly allocated to derivation and validation cohorts. Sex-specific 5-year and 10-year risk prediction models were developed in the derivation cohort and applied in the validation cohort. 28,116 (3.2%) and 62,027 (7.1%) first CVD events occurred during 5-years and 10-years follow-up respectively (cumulative risk, derivation cohort). Median predicted 10-year CVD risk (3.8%) was approximately 2.5 times 5-year risk (1.6%) and 95% of individuals in the top quintile of 5-year risk were also in the top quintile of 10-year risk, across age/gender groups (validation cohort). Using common guideline-recommended treatment thresholds (5% 5-year, 10% 10-year risk), approximately 14% and 28% of women and men respectively were identified as treatment-eligible applying 5-year equations compared to 17% and 32% of women and men applying 10-year equations. Older age was the major contributor to treatment eligibility in both sexes. Predicted 10-year CVD risk was approximately 2.5 times 5-year risk. Both equations identified mostly the same individuals in the highest risk quintile. Conversely, commonly used treatment thresholds identified more treatment-eligible individuals using 10-year equations and both equations identified approximately twice as many treatment-eligible men as women. The treatment threshold, rather than the risk horizon, is the main determinant of treatment eligibility.

Neuroanatomy of the vertebrobasilar perforators: implications for aneurysm treatment.

The anatomy of vertebrobasilar perforators has been widely studied in human cadavers, with most reports found in the neurosurgical literature. These arterial perforators are extremely hard to visualize consistently with traditional two-dimensional digital subtraction angiography, but are reliably visible with cross sectional cone beam CT techniques. A clear understanding of this specific neurovascular anatomy and pathology is essential for informed treatment decisions. This review analyzes the anatomy of vertebrobasilar perforators with a focus on practical implications for aneurysm treatment, particularly flow diversion.

Conventional and Emerging Diagnostic Approaches for Differentiated Thyroid Carcinoma

Differentiated thyroid carcinoma (DTC) is among the most prevalent endocrine cancers. The diagnosis of DTC has witnessed tremendous progress in terms of technological advancement and clinical operational guidelines. DTC diagnostics have evolved significantly over centuries, from early clinical examinations to modern molecular testing and imaging modalities. The diagnosis and management of DTC are currently dependent on the international histological classification and identification of specific genetic abnormalities in tumor tissue, as well as the prognostic implications that can inform treatment decisions. This study goes down the memory lanes of various diagnostic methods for DTCs, highlighting recent advancements in molecular testing and point-of-care (POC) technology. Beginning with conventional methods like fine needle aspiration biopsy (FNAB), fine needle aspiration cytology (FNAC), and ultrasound (US) and moving to contemporary innovative approaches such as POC-thyroglobulin (POC-Tg) and liquid biopsy, this review showcases the current trends in DTC diagnostics. Although considerable progress has been achieved in early malignancy detection, patient stratification, prognosis, and personalized treatment, there is a need to refine the mainstay diagnostic procedures. Finally, future perspectives were provided, and emerging roles of artificial intelligence in DTC diagnostics were explored.

DSTYK Inhibition Sensitizes Non-Small Cell Lung Cancer To Taxane-Based Chemotherapy

Chemotherapy continues to be the standard treatment for patients non-eligible to targeted or immune-based therapies; however, treatment resistance remains a major clinical challenge. We previously found that expression levels of DSTYK, a poorly explored dual serine/threonine and tyrosine kinase frequently amplified in cancer, identifies lung cancer patients exhibiting poor response to immune checkpoint inhibitors and showed that its inhibition sensitizes to immunotherapy. Seeking to explore the potential of DSTYK targeting in additional indications, we investigated the functional relevance and actionability of DSTYK in lung cancer chemoresistance. We show that DSTYK depletion specifically sensitizes lung cancer cells to taxane-based chemotherapy, particularly in combination with carboplatin. Mechanistically, DSTYK ablation remodels the cytoskeleton and impairs distant invasion and metastatic outgrowth in vivo. DSTYK downregulation sensitizes both primary and metastatic lung tumors to chemoimmunotherapy treatment leading to tumor regression in mouse models. Consistently, clinical data of early - in the neoadjuvant and adjuvant settings- and advanced lung cancer patients show a strong correlation between DSTYK amplification and taxane resistance, underscoring the clinical significance of our findings to inform treatment decision-making. Collectively, our data indicates that DSTYK amplification may be a predictor of resistance to taxane-based treatments and represents an actionable target for these patients.

Genomic Epidemiology of Antimicrobial Resistance: Tracking the Global Spread of Resistant Pathogens

The rapid development and spread of antimicrobial resistance have been one of the most prominent health crises globally, which significantly challenges treating infectious diseases. This paper will address the contribution that genomic epidemiology makes to track and understand the global spread of antimicrobial-resistant pathogens. Genomic epidemiology, an area combining pathogen genomics with epidemiological data, allows for an extremely powerful approach in the identification of resistance mechanisms and tracing transmission routes for guiding public health interventions. This review Emphasizes major bacterial pathogens, such as Escherichia coli, Staphylococcus aureus, and Klebsiella pneumoniae, which harbor major resistance genes: blaCTX-M, mecA, and blaKPC. These genes contribute to the worldwide dissemination of resistance, mainly through mechanisms involving horizontal gene transfer and selective antibiotic pressure. Thus, genomic surveillance, phylogenetic analysis, and bioinformatics approaches allow for the pinpointing of transmission hotspots, mapping of resistance gene distribution, and tracking of emerging resistant strains in real time. It also provides information on how genomic data are being used to improve antimicrobial stewardship programs and inform clinical treatment decisions. Public health responses can further be tailored by recognizing regional resistance patterns, hence enhancing interventions. However, several challenges persist—for example, the need for standardized sharing of data, interpretation of genomic data, and integration of these insights into public health systems, especially in low-resource settings. This abstract highlights the transformative impact of genomic epidemiology in the management of the AMR crisis while emphasizing the continued need for global cooperation, enhanced data infrastructures, and policy initiatives to ensure the effective use of genomic data in public health.

Assessment of medical doctors' knowledge of new psychoactive substances and their neurobehavioural effects

New Psychoacve Substances (NPS), also known as designer drugs, pose significant public health risks due to their potent psychoacve properes and potenal neurobehavioural effects. Medical doctors play a crucial role in idenfying and addressing the health risks associated with NPS use. This study assessed medical doctors' knowledge of NPS and their neurobehavioral effects. A cross-seconal online survey of licensed medical doctors was conducted, revealing varying levels of awareness and knowledge regarding NPS. While respondents showed familiarity with NPS terminology and street names, gaps existed, parcularly concerning specific NPS categories. This underscores the importance of enhancing medical professionals' understanding of NPS to ensure comprehensive paent care and informed treatment decisions.

Optimizing the Prediction of Depression Remission: A Longitudinal Machine Learning Approach.

Decisions about when to change antidepressant treatment are complex and benefit from accurate prediction of treatment outcome. Prognostic accuracy can be enhanced by incorporating repeated assessments of symptom severity collected during treatment. Participants (n = 714) from the Genome-Based Therapeutic Drugs for Depression study received escitalopram or nortriptyline over 12 weeks. Remission was defined as scoring ≤ 7 on the Hamilton Rating Scale. Predictors included demographic, clinical, and genetic variables (at 0 weeks) and measures of symptom severity (at 0, 2, 4, and 6 weeks). Longitudinal descriptors extracted with growth curves and topological data analysis were used to inform prediction of remission. Repeated assessments produced gradual and drug-specific improvements in predictive performance. By Week 4, models' discrimination in all samples reached levels that might usefully inform treatment decisions (area under the receiver operating curve (AUC) = 0.777 for nortriptyline; AUC = 0.807 for escitalopram; AUC = 0.794 for combined sample). Decisions around switching or modifying treatments for depression can be informed by repeated symptom assessments collected during treatment, but not until 4 weeks after the start of treatment.

Clinical value of comprehensive genomic profiling on clinical trial enrollment for patients with advanced solid tumors.

The use of biomarker testing to inform treatment decisions has emerged as a standard of care in multiple cancer types. However, the rates of patients with genomic testing results in hand to inform treatment decision-making remain variable. Here, we studied the impact of comprehensive genomic profiling (CGP) on clinical trial enrollment rates in patients with advanced-stage non-small cell lung, colorectal, breast, and prostate cancer using a real-world clinicogenomic database. On average, clinical trial enrollment in the therapy line immediately after CGP report receipt was 5.4%, which represents a 3.0 percentage point increase compared to therapy lines preceding CGP report receipt, supporting a meaningful association between CGP report availability and increased clinical trial enrollment.

Predictive power of the eTBI score for 30 day outcome in elderly patients with traumatic brain Injury

Traumatic brain injury (TBI) is a common problem in elderly individuals, with significant morbidity and mortality. The elderly Traumatic Brain Injury (eTBI) score, a novel tool for predicting outcomes in elderly patients with TBI, has shown promising results in previous studies. This study aimed to validate the eTBI score in a larger cohort of elderly patients with TBI in the Middle East. We conducted a retrospective study on 337 TBI patients with a mean age of 73.04 ± 8.73, admitted to a tertiary care hospital between March 2021 and November 2022. Within 30 days of admission, the patients’ conditions, including mortality and entering a vegetative state, were evaluated. The study population was split into three groups based on eTBI score: low, medium, and high risk; then patients were divided into two subgroups based on their Glasgow Outcome Scale (GOS ≤ 2, GOS > 2) in 30 days from hospital admission. Poor outcomes (mortality and entering a vegetative state) occurred in 24.3% of the study population. Within 30 days of hospital admission, 88% of low-risk patients experienced some degree of improvement, while 100% of high-risk patients died or fell into a vegetative state. In the medium-risk group, there was a significant correlation between unresponsive pupil (P = 0.006), initial GCS score (P = 0.003), need for a ventilator device (P = 0.015), need for surgical treatment (P = 0.031) and poor outcomes. Despite having a low sensitivity (21% vs. 57%), the eTBI score performed well in terms of accuracy (81% vs. 88%), specificity (100 vs. 98%), positive predictive value (100% vs. 90%), and negative predictive value (80% vs. 88%) for both eTBI ≤ 0 and eTBI ≤ 3 thresholds. The eTBI score is a reliable tool for predicting outcomes in elderly patients with TBI. This scoring system has a positive predictive value of 100% in the eTBI ≤ 0 group, which shows that 100% of the patients who are predicted by the eTBI score to have a poor outcome will indeed have a poor outcome. Patients in the high-risk group should be closely monitored and provided with intensive care, while those in the low-risk group can be reassured about their prognosis. The eTBI score can also be used in conjunction with other clinical factors to inform treatment decisions for patients in the medium-risk group.

Comparative Diagnostic Value of 18F-FDG–PET–CT and Intraoperative Examination in Cervical Cancer Staging

Background and Objectives: The primary objective of this study is to assess the effectiveness of 18F-FDG–PET–CT in preoperative staging of cervical cancer, focusing on determining surgical operability and exploring the correlation between its quantitative parameters and clinicopathological characteristics. Materials and Methods: This retrospective study included 62 cervical cancer patients treated at the Department of Gynecology, Clinic for Operative Oncology at the Institute of Oncology Vojvodina between January 2016 and January 2020, where preoperative clinical examinations and 18F-FDG–PET–CT were performed to assess the extent of cancer, followed by intraoperative and pathohistological examinations of surgically removed specimens to provide a comprehensive evaluation. Results: The mean tumor size measured by 18F-FDG–PET–CT was slightly greater than that obtained through clinical examination (26.4 mm vs. 26.0 mm), with a strong linear correlation (r = 0.678, p < 0.001) observed between the two measurement methods. The overall prediction accuracy of 18F-FDG–PET–CT for primary tumors is 88.7% (55/62) [sensitivity 86.8%, specificity 100.0%, PPV 100.0%, NPV 56.2%] and for intraoperative examination is 88.7% (55/62) [sensitivity 98.1%, specificity 33.3%, PPV 89.7%, NPV 75.0%]. The agreement with histopathological examination was good for 18F-FDG–PET–CT and moderate for intraoperative examination for primary tumors. Regarding lymph nodes, the overall prediction accuracy of 18F-FDG–PET–CT is 82.2% (51/62) [sensitivity 53.8%, specificity 89.8%, PPV 58.3%, NPV 88.8%] and for intraoperative examination 66.1% (41/62) [sensitivity 76.9%, specificity 63.3%, PPV 35.7%, NPV 91.2%]. The agreement with histopathological examination was moderate for 18F-FDG–PET–CT and poor for intraoperative examination for lymph node metastasis, highlighting that the overall accuracy of 18F-FDG–PET–CT (82.1%) was significantly higher than that of intraoperative examination (66.1%) (p = 0.002). Conclusions: In conclusion, 18F-FDG–PET–CT provides high accuracy in detecting primary tumors and superior predictive value for lymph node metastases compared to intraoperative examination, highlighting the importance of incorporating this imaging modality into the preoperative evaluation process to enhance diagnostic precision and inform treatment decisions.

Advancing Frontiers in Colorectal Cancer: Exploring Novel Insights and Emerging Trends in Research and Therapy

Colorectal cancer, a known form of cancer poses a global health threat. Ongoing studies are actively investigating perspectives and evolving treatments. This review explores the developments in cancer research covering topics such as profiling, microbiome interactions, immunotherapy, precision medicine, tumor environment analysis, liquid biopsies, metabolic changes, artificial intelligence applications and patient centric care. Molecular subtyping advancements have greatly improved our understanding of the nature of cancer and how different individuals respond to therapies. The significant link between gut microbiome composition, inflammation levels and immune responses underscores the importance of interventions targeting the microbiome and innovative immunotherapy strategies. Precision medicine initiatives are leveraging biomarkers and molecular signals to inform treatment decisions and optimize outcomes. This thorough examination highlights the impact of evolving trends in cancer research and treatment strategies while offering insights into directions for improving patient care and results.Keywords: Cancer research; Microbiome interaction; Immunotherapy; Liquid biopsy; Biomarkers

Early use of long-acting injectable antipsychotics in bipolar disorder type I: An expert consensus.

Long-acting injectable antipsychotics (LAIs) are not routinely offered to patients living with bipolar disorder type I (BP-I), despite widespread evidence that supports their benefits over oral antipsychotics, particularly in early disease. A round-table meeting of psychiatrists convened to discuss barriers and opportunities and provide consensus recommendations around the early use of LAIs for BP-I. LAIs are rarely prescribed to treat BP-I unless a patient has severe symptoms, sub-optimal adherence to oral antipsychotics, or has experienced multiple relapses. Beyond country-specific accessibility issues (e.g., healthcare infrastructure and availability/approval status), primary barriers to the effective use of LAIs were identified as attitudinal and knowledge/experience-based. Direct discussions between healthcare providers and patients about treatment preferences may not occur due to a preconceived notion that patients prefer oral antipsychotics. Moreover, as LAIs have historically been limited to the treatment of schizophrenia and the most severe cases of BP-I, healthcare providers might be unaware of the benefits LAIs provide in the overall management of BP-I. Improved treatment adherence associated with LAIs compared to oral antipsychotics may support improved outcomes for patients (e.g., reduced relapse and hospitalization). Involvement of all stakeholders (healthcare providers, patients, and their supporters) participating in the patient journey is critical in early and shared decision-making processes. Clinical and database studies could potentially bridge knowledge gaps to facilitate acceptance of LAIs. This review discusses the benefits of LAIs in the management of BP-I and identifies barriers to use, while providing expert consensus recommendations for potential solutions to support informed treatment decision-making.

Targeted next-generation sequencing - a promising approach in the diagnosis of Mycobacterium tuberculosis and drug resistance.

Targeted next-generation sequencing (tNGS) offers a high-throughput, culture-independent approach that delivers a comprehensive resistance profile in a significantly shorter turn-around time, making it promising in enhancing tuberculosis (TB) diagnosis and informing treatment decisions. This study aims to evaluate the performance of tNGS in the TB diagnosis and drug resistance detection of Mycobacterium tuberculosis (MTB) using MTB clinical isolates and bronchoalveolar lavage fluid (BALF) samples. A total of 143 MTB clinical isolates were assessed, tNGS, phenotypic antimicrobial susceptibility testing (AST), and AST based on whole genome sequencing (WGS) exhibited high concordance rates, averaging 95.10% and 97.05%. Among 158 BALF samples, culture, Xpert MTB/RIF, and tNGS reported 29, 70 and 111 positives, respectively. In the confirmed cases with etiological evidence (smears, cultures, or molecular test), the positive rate of tNGS (73/83, 87.95%) was higher than that of Xpert MTB (67/83, 80.72%). Additionally, 45% (27/60) of clinically diagnosed cases (with imaging or immunological evidence) were positive for tNGS. Further validation on the discrepant results between tNGS and Xpert MTB/RIF with droplet digital PCR (ddPCR) yielded 35 positives, tNGS detected all, and Xpert MTB/RIF only identified 6 positives. In conclusion, tNGS demonstrates robust and rapid performance in the identification of MTB and its associated drug resistance, and can be directly applied to clinical samples, positioning it as a promising approach for laboratory testing of tuberculosis.

Palbociclib plus aromatase inhibitors in patients with metastatic breast cancer and cardiovascular diseases: real-world effectiveness.

Patients with cardiovascular disease (CVD) comorbidities are often excluded from participating in breast cancer clinical trials. Consequently, data to inform treatment decisions for patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) metastatic breast cancer (mBC) and CVD are limited. We compared the effectiveness of first-line palbociclib plus an aromatase inhibitor (AI) vs an AI alone and evaluated palbociclib treatment patterns in patients with HR+/HER2- mBC and CVD in routine clinical practice. Data from the Flatiron Health Analytic Database were captured for patients with HR+/HER2- mBC and CVD who initiated first-line treatment with palbociclib plus an AI or an AI alone between February 2015 and March 2020 (data cutoff: September 30, 2020). Overall survival (OS), real-world progression-free survival (PFS), and treatment patterns were evaluated. Of the 469 patients with identifiable CVD, 160 received palbociclib plus an AI, and 309 received an AI alone. After stabilized inverse probability treatment weighting, both median OS (40.7 vs 26.5 months; hazard ratio [HR], 0.732 [95% CI, 0.537-0.997]; P = .048) and median real-world PFS (20.0 vs 12.5 months; HR, 0.679 [95% CI, 0.512-0.900]; P = .007) were significantly prolonged in patients treated with palbociclib plus an AI vs an AI alone. Among patients with a documented palbociclib starting dose, 78.5% started palbociclib at 125mg/day, and 38.6% experienced dose adjustment. In this real-world analysis, first-line palbociclib plus an AI was associated with improved effectiveness compared with an AI alone in patients with HR+/HER2- mBC and CVD. NCT05361655 (ClinicalTrials.gov).

Advancing radiation therapy safety in cancer-care: Leveraging AI for adverse reaction prediction

The development of advanced technologies for radiation cancer treatment plays a pivotal role in anticipating potential complications, safeguarding patient well-being, and elevating treatment satisfaction. Access to curated medical data coupled with specialized knowledge in radiation oncology is indispensable for equipping healthcare professionals with the insights needed to make informed treatment decisions. This study endeavors to provide systematic support to practitioners in predicting personalized side effects of radiation oncology treatments before their administration to patients. For this, a pioneering ontology-based methodology for evidence-based medicine is introduced, drawing upon information and evidence from various scientific outlets. This approach utilizes semantic modeling and rule-based reasoning to assess radiation therapy pathways, ensuring adjustments are made when necessary to mitigate health risks and enhance safety. Focused on radiation oncology, the intricacies of knowledge are simplified and validated through real reported cases obtained from scientific literature. The resulted predictive model demonstrated a notable compatibility rate of 76.7% with real reported risks, surpassing conventional methods by 4% during testing achieves 89% success with single therapies but faces challenges with complex regimens. Data enrichment may increase accuracy by 20% over five years. Current method accuracy is 92%, with potential for 97% through quantum-inspired methods. Testing reveals 80.1% compatibility, exceeding conventional approaches by 3%. These findings hold significant potential of ontology-based models for revolutionizing radiation oncology treatment strategies in the realm of radiation protection.

Validity assessment of a third-generation light-induced fluorescence device in detecting proximal and occlusal caries lesions: A cross-sectional study

ObjectivesThe objective of this study was to evaluate the efficacy of a quantitative light-induced fluorescence (QLF) device (QrayCam Pro, AIOBIO, Seoul, Republic of Korea) in detecting and differentiating the severity of posterior proximal and occlusal primary caries. Materials and methodsThe study included a total of 120 teeth in 60 patients (of both genders, aged between 21 and 38 years) between January and March 2024, one carious tooth and one sound tooth were selected at random in each patient. All occlusal surfaces were evaluated in accordance with the International Caries Detection and Assessment System (ICDAS) Nyvad Criteria, using the visual tactile method. The ICDAS employs a scoring system ranging from 0 to 6, while the Nyvad Criteria employs a similar scoring system. Addionally, the depth of the proximal lesions was scored (0–6) using bite-wing radiography. The quantitative values representing the maximum loss of fluorescence (∆Fmax) and the maximum change in the ratio of red and green fluorescence (∆Rmax) were obtained using the Q-ray Clinical software v 1.45. To assess the validity, the sensitivity, specificity, and area under the receiver operating characteristics curve (AUROC) were calculated. Spearman correlation coefficient was used to investigate the correlation between the findings of the traditional and QLF examination methods. ResultsThe AUROC values for both ∆Fmax and ∆Rmax were found to be excellent. The sensitivity of QrayCam Pro was found to be 84–88.6%, while the specificity was 100%. The correlation analysis demonstrated a strong correlation between scores obtained from the traditional examination and the QLF values. ConclusionsBased on the findings of this study, QrayCam Pro exhibits potential as a valuable additional tool for not only detecting caries but also for assessing their severity and activity. Clinical relevanceThis study revealed that QrayCam Pro might be suggested as a precise tool for enhancing caries detection and assessment compared to traditional methods. By providing quantitative data on caries severity and activity, it enables more informed treatment decisions, potentially optimizing outcomes for patients.