CORE--PROGNOSTIC MODELING

核心——预测建模

• 批准号: 6336446
• 负责人: LAWRENCE H EINHORN
• 金额: $ 12.86万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-01 至 2001-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6336446
• 关键词: biomedical facility; germ cell neoplasms; mathematical model; model design /development; prognosis

DESCRIPTION: (Applicant's Description) Germ cell tumors have been held up as a model of a curable malignancy. In addition to effective chemotherapy, successful management of this tumor has come to depend on careful definition of prognosis based on available clinical parameters. Despite a great deal of effort, the utility of these clinically-based prognostic systems has been maximized and still are associated with a 10-50 percent error rate in correctly predicting patient outcome. Newly available technologies have led to discoveries of biological and molecular events in cancer initiation, growth and metastasis, but only rarely have these discoveries been coupled to clinical outcome or led to the discovery of therapeutic targets in solid tumors. The ability to identify circulating solid tumor cells and explore genetic alterations in germ cell tumors affords the opportunity to correlate these biologic and molecular insights into issues of clinical care. We hypothesize that these new technologies can identify biological endpoints that can substantially augment or even supersede currently available clinically-based prognostic systems. A more accurate prognostic system would have significant ramifications in the selection of patients for more aggressive surgeries and treatments, and sparing some patients the rigors of such treatments. We propose to analyze molecular data obtained from the three scientific Projects in this Program in conjunction with existing clinical parameters. At completion, we will integrate these new findings into current clinical prognostic models.

描述：（申请人的描述）生殖细胞肿瘤已被视为可治愈恶性肿瘤的模型。 除了有效的化疗外，该肿瘤的成功管理还取决于基于可用临床参数的预后定义。尽管付出了很大的努力，但这些基于临床的预后系统的实用性已最大化，并且在正确预测患者预后的情况下仍然与10-50％的错误率有关。新近可用的技术导致了癌症开始，生长和转移中生物学和分子事件的发现，但只有这些发现很少与临床结果耦合或导致实体瘤中的治疗靶标。 鉴定循环实体瘤细胞并探索生殖细胞肿瘤中的遗传改变的能力，有机会将这些生物学和分子见解与临床护理问题相关联。 我们假设这些新技术可以识别可以大大增加甚至取代当前可用的基于临床的预后系统的生物终点。一个更准确的预后系统将在选择患者进行更具侵略性的手术和治疗方面的选择，并为某些患者提供严格的治疗方法。 我们建议分析从该程序中的三个科学项目获得的分子数据以及现有的临床参数。 完成后，我们将将这些新发现集成到当前的临床预后模型中。