To define the characteristics of CSCs | Establish a common conceptual framework for evaluating the measurement of CSCs. Determine the specific characteristics to define a CSC and develop an operational definition for a CSC in pediatric oncology. Identify the sentinel symptom within a CSC. Evaluate the relationship between signs (objective indications) and symptoms (subjective sensations) within a CSC. Evaluate for CSC in defined patient subgroups in pediatric oncology. Develop qualitative approaches to identify and prioritize CSCs according to their importance to patients. Develop a consistent approach to identify patient subgroups based on a pre-specified CSC. Identify the most common de novo CSCs in pediatric oncology. Replicate studies of subgroups of pediatric cancer patients with similar and different experiences with a prespecified CSC; tailor assessment, interventions, and outcome measures to the evolving CSC over the course of childhood cancer. Determine the phenotypic as well as molecular predictors and/or risk factors for the development of prespecified CSC in pediatric cancer patients under different types of antineoplastic therapies. Evaluate the potential for using large data sets and the electronic health record to assess CSC. Develop and test methods to assess CSC in pediatric cancer patients who cannot self-report symptoms. Develop and test methods to assess CSC using surrogates for CSC reporting (e.g., physicians, nurses, family caregivers, informal caregivers).
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To prioritize CSCs and their underlying its mechanisms | Develop a core set of symptom inventories for CSC research in pediatric oncology. Evaluate the molecular mechanisms underlying CSC, including (I) inflammation/immune system, (II) hypothalamic-pituitary-adrenal axis activation, (III) sympathetic nervous system activation, (IV) central nervous system alterations, (V) circadian rhythm alterations, etc. Determine the best approaches to evaluate the underlying genetic and epigenetic mechanisms for CSC in pediatric oncology. Determine the best methods to assess the biobehavioral mechanisms for CSC in pediatric oncology. Develop and evaluate animal models of CSC in pediatric oncology. Determine whether common mechanisms exist for CSC in pediatric oncology. Develop a systematic approach for biomarker selection for CSC research in pediatric oncology.
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Appropriately and reliably measure the CSCs | Use qualitative methods to identify common and disease-specific CSC across the pediatric cancer spectrum. Develop generic and disease-specific measures to assess CSC in pediatric oncology. Determine the optimal approach to data collection for CSC research in pediatric oncology. Compare and contrast the number and types of CSCs, as well as changes over time, identified in pediatric cancer patients using a variety of analytical techniques. Evaluate the validity, reliability, and responsiveness of PROMIS measures in pediatric oncology CSC research. Establish a common core data set for pooling data and assessing data comparability across pediatric oncology CSC studies. Use new methods to refine measures for CSC (e.g., Rasch analysis). Establish red-flag values for CSC that warrant intervention(s) for pediatric cancer patients. Correlate various outcomes of CSC (e.g., functional status, social status, quality of life, mortality, survival, costs, health care utilization, patient satisfaction, and caregiver burden).
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To evaluate the effective targeted interventions for CSC management | Evaluate the use of new trial designs to determine if they can be used to tailor interventions to treat single or multiple symptoms within a CSC in pediatric oncology. Determine the most effective interventions for different pediatric oncology CSCs. Determine the most appropriate outcome for a pediatric oncology CSC intervention trial. Evaluate the use of technology in pediatric oncology CSC research.
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To propose new advanced analytical techniques for better assessment of CSCs in research | Applying new analytical techniques to pediatric oncology CSC research (e.g., latent transition analysis, evolutionary algorithms, machine learning, and risk stratification). Establish guidelines for the selection of optimal analytic strategies for CSC research in pediatric oncology.
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