Search

Background: Despite the favorable prognosis of AJCC stage I/II melanoma patients, up to 20%–30% will develop metastases. Our objective is to predict long‐term risk (probability) of recurrence in early‐stage melanoma patients. Methods: A Risk Score to predict long‐term recurrence was developed using Cox regression based on 2668 patients. Five clinicopathological risk factors were included. The association of the Risk Score with the risk of recurrence was evaluated using parametric models (exponential, Weibull, and Gompertz models) and compared to the Cox model using the Akaike information criterion. The discrimination of the model was measured by time‐dependent ROC analyses. A calibration curve was used to evaluate the agreement between predicted and observed recurrence probabilities. Results: The bootstrap adjusted C‐index was 0.76 (95% CI, 0.74–0.79) overall and 0.87 (0.83–0.90) and 0.82 (0.78–0.85) at one and two years, respectively, and then remained above 0.70 up to 20 years. The Gompertz model for prediction of survival from the Risk Score showed the best performance and displayed good agreement with the Kaplan–Meier curves. The calibration curve of the Gompertz model showed a good agreement between predicted and observed 2‐, 5‐, and 10‐year risk of recurrence. Population‐level analysis demonstrated a significant association of Risk Score with risk of recurrence, with 10‐year risks of recurrence of 4.5%, 13.0%, and 33.7% in the first, second, and third tertiles, respectively. Conclusion: We developed a Risk Score to predict long‐term risk of recurrence for early‐stage melanoma patients. A Gompertz survival model fit to the Risk Score allows for individualized prediction of time‐dependent recurrence risk. [ABSTRACT FROM AUTHOR]

The limited success of immune checkpoint inhibitors (ICIs) in the adjuvant setting for glioblastoma highlights the need to explore administering ICIs prior to immunosuppressive radiation. To address the feasibility and safety of this approach, we conducted a phase I study in patients with newly diagnosed Grade 3 and Grade 4 gliomas. Patients received nivolumab 300 mg every 2 weeks and ipilimumab 1 mg/kg every 6 weeks until disease progression or unacceptable toxicity. Fifteen patients were treated, with four patients on dexamethasone at treatment initiation and five tumors having MGMT promoter methylated. Treatment began a median of 38 days post-surgery. The most common treatment-related adverse events (AEs) were rash, pruritus, fatigue, nausea, and anorexia. Grade 3 AEs were lipase increased (n = 2), anorexia (n = 1), pruritus (n = 1), and rash (n = 3), and one Grade 4 cerebral edema occurred. Median progression-free survival (mPFS) was 1.3 months and median overall survival (mOS) was 19.3 months (95% CI, 12.9-NA). Three patients deferred conventional radiochemotherapy for over seven months while ten eventually received it. Progressing tumors tended to exhibit higher LAG-3 levels at baseline compared to shrinking tumors. Analysis of paired pre-treatment and post-progression tissue (n = 5) showed trends of up-regulated TGF-β, ERBB2, ERBB3, and ERBB4 signaling pathways, downregulated PPAR signaling, decreased B cell proportions, and increased monocytes proportions in tumors post-treatment. We show nivolumab plus ipilimumab can be safely administered prior to standard radiotherapy for newly diagnosed gliomas and is operationally feasible. Clinicaltrials.gov NCT03425292 registered February 7, 2018. [ABSTRACT FROM AUTHOR]

PURPOSE: Precision therapies and immunotherapies have revolutionized cancer care, with novel genomic biomarker-associated therapies being introduced into clinical practice rapidly, resulting in notable gains in patient survival. Despite this, there is significant variability in the utilization of tumor molecular profiling that spans the timing of test ordering, comprehensiveness of gene panels, and clinical decision support through therapy and trial recommendations. METHODS: To standardize testing, we designed a pathologist-directed test ordering system at the time of diagnosis using a 523-gene DNA/RNA hybrid comprehensive genomic profiling (CGP) panel and extensive clinical decision support tools. To comprehensively characterize the clinical impact of this protocol, we developed a novel natural language processing (NLP)–based approach to extract clinical features from physician chart notes. We assessed test actionability rates, therapy choice, and outcomes across a set of 3,216 patients with advanced cancer. RESULTS: We observed 49% of patients had at least one actionable genomic biomarker-driven–approved and/or guideline-recommended targeted or immunotherapy (IO) and 53% of patients would have been eligible for a precision therapy clinical trial from three large basket trials. When assessing CGP versus an in silico 50-gene panel, 67% of tumors compared with 33% harbored actionable alterations including clinical trials. Among patients with 6 months or more of follow-up, over 52% received a targeted therapy (TT) or IO, versus 32% who received conventional chemotherapy alone. Furthermore, patients receiving TT had significantly improved overall survival compared with patients receiving chemotherapy alone (P <.001). CONCLUSION: Overall, these data represent a major shift in standard clinical practice toward molecularly guided treatments (targeted and immunotherapies) over conventional systemic chemotherapy. As guidelines continue to evolve and more precision therapeutics gain approval, we expect this gap to continue to widen. Current utilization patterns for tumor genomic testing are highly variable because of a variety of factors including lack of access and socioeconomic barriers. Here, we developed a program to attempt to remove many of these barriers and provide genomic testing rapidly as possible. Evaluating results over a multiyear period, we found around half of the patients tested with comprehensive genomic profiling had an actionable biomarker. Tested patients also received precision therapies at a higher rate than conventional chemotherapy alone, which was associated with higher overall survival across the real-world cohort. [ABSTRACT FROM AUTHOR]

The World Health Organization emphasizes the importance of providing integrated care for older people. Taiwan is the fastest aging country in the world. In 2016, Taiwan implemented the Long-Term Care Plan 2.0 (TLTCP 2.0), aimed at providing integrated long-term care (LTC) services in communities. However, LTC service agencies have not been able to evaluate the level of integrated care they provide due to the lack of an effective assessment tool. To address this need, this study sets out to develop an integration assessment tool, namely the Self-Assessment for Service Integration in Long-Term Care (SASI-LTC), which will allow LTC agencies to self-evaluate their current level of integration from multiple perspectives. The SASI-LTC was developed based on Evashwick's framework, underwent two rounds of Delphi panels with twenty-six experts, and a pilot test with 243 valid questionnaires from administrators of Tier A agencies who are responsible for integrating LTC. The Delphi experts assessed the content with high levels of agreement using medians, the scale content validity index (SCVI) and item content validity index (ICVI). The SASI-LTC included four domains (inter-entity organization and management, integrated care coordination, integrated resources, and integrated information systems) with thirty items. The SASI-LTC showed good reliability (Cronbach's α = 0.94) and good validity, and a confirmatory factor analysis showed a good model fit index [χ2/df = 1.38; RMSEA = 0.040; CFI = 0.963; SRMR = 0.049] in pilot testing. While the SASI-LTC is a useful and feasible tool for Taiwan's LTC service agencies to evaluate their level of integration in providing LTC services, it could also be used in other countries with minor adjustments to localization of items related to financial integration. [ABSTRACT FROM AUTHOR]

The Common Core State Standards suggest that an appropriate goal for secondary education is college and career readiness. Previous research has identified reading fluency as a critical component for proficient reading. One component of fluency is word recognition accuracy and automaticity. The present study attempted to determine the word recognition accuracy and automaticity indicators for incoming college students and to examine the relationship between oral reading rate and ACT scores. Knowledge of such performance may provide secondary literacy educators with another tool for assessing reading proficiency and college readiness. Eighty-one students were asked to read a college-level narrative passage. Mean student accuracy and automacity scores were determined, as well as correlations between accuracy, automacity, and students' ACT scores. Results suggest a moderate and significant relationship between measures of automaticity and both the ACT reading subtest and ACT composite scores.