371 Background: Prostate cancer is the most common malignancy in men globally and remains among the top five leading causes of cancer-related deaths. Emerging evidence suggests that early identification of symptoms can detect localized disease thus enabling opportunities for curative intent treatments. This study evaluates the use of the AI-powered prediction model, C the Signs, to passively screen for prostate cancer by leveraging data from electronic medical records (EMRs), offering a novel pathway for identifying high-risk individuals. Methods: A retrospective analysis was conducted using the Mayo Data Platform, encompassing 418,477 male patient records, of which 16,835 were diagnosed with prostate cancer. C the Signs identified patients at risk based solely on their EMR data, utilizing AI-driven pattern recognition. Sensitivity and specificity analyses were performed to assess the prediction model’s accuracy. Additionally, we examined the time-to-diagnosis advantage for patients flagged by the model compared to traditional physician clinical diagnoses. Results: C the Signs demonstrated a sensitivity of 83.3% and a specificity of 52.5% for identifying patients at risk of prostate cancer. Notably, 31.8% of prostate cancer cases were identified at risk up to five years earlier by the model compared to traditional physician clinical diagnosis. Conclusions: The integration of AI-driven prediction models like C the Signs into prostate cancer screening pathways provides an opportunity to enhance early detection, particularly in symptomatic individuals. Compared to prostate-specific antigen (PSA) testing, the model achieved equivalent sensitivity and 38% higher specificity, positioning it as a valuable companion tool for improving patient outcomes.
Summary The opioid receptor (OR) antagonist naltrexone inhibits estrogen receptor-α (ER) function in model systems. The goal of this study was to determine the clinical activity of naltrexone in patients with ER-positive metastatic breast cancer. Patients with hormone receptor positive metastatic breast cancer were enrolled on a phase II study of naltrexone. An escalating dose scheme was used to reach the planned dose of 50 mg daily. The primary objective of the study was to evaluate response to therapy as measured by stabilization or reduction of the tumor Maximum Standardized Uptake Value (SUVmax) at 4 weeks by PET-CT scan. The secondary objectives included safety assessment and tumor SUVmax at 8 weeks. Out of 13 patients we enrolled, 8 patients had serial PET-CT scans that were evaluable for response. Of these 8 patients, 5 had stable or decreased SUVmax values at 4 weeks and 3 had clinical or imaging progression. Median time to progression was short at 7 weeks. Naltrexone was well tolerated. There were no discontinuations due to toxicity and no grade 3 or 4 toxicities were noted. Naltrexone showed modest activity in this short study suggesting the contribution of opioid receptors in ER-positive breast cancer. Our data do not support further development of naltrexone in hormone refractory breast cancer. It is possible that more potent peripherally acting OR antagonists may have a greater effect. ( ClinicalTrials.gov Identifier: NCT00379197 September 21, 2006 ).
BACKGROUND Screening patients for eligibility for clinical trials is labor intensive. It requires abstraction of data elements from multiple components of the longitudinal health record and matching them to inclusion and exclusion criteria for each trial. Artificial intelligence (AI) systems have been developed to improve the efficiency and accuracy of this process. OBJECTIVE This study aims to evaluate the ability of an AI clinical decision support system (CDSS) to identify eligible patients for a set of clinical trials. METHODS This study included the deidentified data from a cohort of patients with breast cancer seen at the medical oncology clinic of an academic medical center between May and July 2017 and assessed patient eligibility for 4 breast cancer clinical trials. CDSS eligibility screening performance was validated against manual screening. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for eligibility determinations were calculated. Disagreements between manual screeners and the CDSS were examined to identify sources of discrepancies. Interrater reliability between manual reviewers was analyzed using Cohen (pairwise) and Fleiss (three-way) κ, and the significance of differences was determined by Wilcoxon signed-rank test. RESULTS In total, 318 patients with breast cancer were included. Interrater reliability for manual screening ranged from 0.60-0.77, indicating substantial agreement. The overall accuracy of breast cancer trial eligibility determinations by the CDSS was 87.6%. CDSS sensitivity was 81.1% and specificity was 89%. CONCLUSIONS The AI CDSS in this study demonstrated accuracy, sensitivity, and specificity of greater than 80% in determining the eligibility of patients for breast cancer clinical trials. CDSSs can accurately exclude ineligible patients for clinical trials and offer the potential to increase screening efficiency and accuracy. Additional research is needed to explore whether increased efficiency in screening and trial matching translates to improvements in trial enrollment, accruals, feasibility assessments, and cost.
<div>AbstractPurpose:<p>We previously reported that postmenopausal women with estrogen receptor-α–positive breast cancer receiving adjuvant anastrozole 1 mg/day (ANA1) with estrone (E1) ≥1.3 pg/mL and estradiol (E2) ≥0.5 pg/mL [inadequate estrogen suppression (IES)] had a threefold increased risk of a breast cancer event. The objective of this study was to determine if increasing anastrozole to 10 mg/day (ANA10) could result in adequate estrogen suppression (AES: E1 <1.3 pg/mL and/or E2 <0.5 pg/mL) among those with IES on ANA1.</p>Patients and Methods:<p>Postmenopausal women with estrogen receptor-α–positive breast cancer planning to receive adjuvant ANA1 were eligible. E1 and E2 were assessed pre- and post-8 to 10 weeks of ANA1. Those with IES were switched to 8- to 10-week cycles of ANA10 followed by letrozole 2.5 mg/day. E1 and E2 were assessed after each cycle. Anastrozole concentrations were measured post-ANA1 and post-ANA10. Primary analyses included patients who documented taking at least 80% of the planned treatment (adherent cohort).</p>Results:<p>In total, 132 (84.6%) of 156 eligible patients were ANA1 adherent. IES occurred in 40 (30.3%) adherent patients. Twenty-five (78.1%) of 32 patients who began ANA10 were adherent, and AES was achieved in 19 (76.0%; 90% confidence interval, 58.1%–89.0%) patients. Anastrozole concentrations post-ANA1 and post-ANA10 did not differ by estrogen suppression status among adherent patients. AES was maintained/attained in 21 (91.3%) of 23 letrozole-adherent patients.</p>Conclusions:<p>Approximately 30% of ANA1-adherent patients had IES. Among those who switched to ANA10 and were adherent, 76% had AES. Further studies are required to validate emerging data that ANA1 results in IES for some patients and to determine the clinical benefit of switching to ANA10 or an alternative aromatase inhibitor.</p></div>
Abstract BACKGROUND Central nervous system (CNS) tumors are frequently characterized by physical disabilities, and treatment is often associated with side effects, as well as financial toxicity and loss of income owing to disease-related neurological deficits. Treatment at centers with specialized neuro-oncology care is associated with an overall survival benefit. However, access to such centers can be limited for many patients. Telehealth services represent an option for improving access to specialized care. During the COVID-19 pandemic public health emergency (PHE), regulatory and reimbursement changes provided patients improved access to neuro-oncology by telehealth. METHODS We retrospectively analyzed our institutional utilization of telehealth visits in the neuro-oncology vs solid tumor oncology practice after the COVID-19 pandemic. RESULTS Between July 2020 and April 2021, telehealth represented 24.1% of all neuro-oncology visits compared to 13.3% for all solid tumor groups. Between May 2021 and April 2023, telehealth visits remained frequent in neuro-oncology compared to solid tumor groups (34.6% vs 15.2%). Utilization rates declined across the practice in the year following expiration of the COVID-19 PHE in May 2023, though remained high for neuro-oncology at 34.1% vs 15.2% for solid tumor groups. Overall, telehealth visit utilization for neuro-oncology has remained more than double that of the oncology practice as a whole. CONCLUSIONS The striking difference between telehealth visit utilization in neuro-oncology compared with general medical oncology indicates that patients with CNS tumors, and those that provide care for these patients, have come to depend on this mode of care delivery. Even after expiration of the COVID-19 PHE, telehealth use remains high in neuro-oncology at our institution. Prospective evaluation to determine the safety of and clinical outcomes associated with telehealth visits for individuals with CNS tumors are critically needed. Such data may promote regulatory and reimbursement reform enabling broader adoption, service sustainability, and improved access to specialized care.
9048 Background: Young women with a new diagnosis of cancer grapple with several important issues when deciding on treatment options. For pre-menopausal women, the risks of infertility and premature menopause due to cancer therapy are frequently overlooked in physician-patient discussions during treatment planning. Methods: We designed a 24 item questionnaire to assess the frequency and quality of discussions of cancer therapy impact on fertility, menopausal status and general sexual health and distributed it in 4 oncology clinics: breast cancer, gynecologic oncology, general oncology, and bone marrow transplant (BMT). Participants had to be pre-menopausal at diagnosis and within 24 months of completing cancer treatment. Results: Completed questionnaires were obtained from 114 women of 126 screened, and 10 were excluded from analysis due to ineligibility. Overall, 66% of women were satisfied with the quality and length of reproductive health discussions, with lowest satisfaction levels in BMT (53%) and highest in gynecologic clinics (85%). Of those women with a male oncologist, 23% reported dissatisfaction with the quality of discussions as compared with 13% of those with a female oncologist. A relatively large proportion of women desired to preserve fertility during treatment, including 46% >35 years, 18% 35-39 years and 15% ≥40 years of age. Risk of infertility influenced choice of therapy in 14% of all women. Overall, 33% of women wanted to discuss and 70% reported physician discussion of impact of therapy on fertility. Of the women who were not interested in becoming pregnant, 8% ranked fertility issues as important to discuss. Also, 56% wanted to discuss and 35% reported physician discussion of impact of therapy on sexual health. More than half of all women sought out additional resources on these topics. Conclusions: Most oncologists address cancer therapy impact on fertility during treatment planning discussions. However, there is a relative lack of discussion between physicians and women about its impact on general sexual health. Satisfaction regarding discussions on these topics may vary depending on oncologic specialty clinic, a woman's age, and the gender of her oncologist. No significant financial relationships to disclose.
