A quality of life subscale for terminally ill cancer patients

A subscale was developed to assess the quality of life of cancer patients with a life expectancy of six months or less. Phase I of this study identified the major concerns of 74 terminally ill cancer patients (19 with breast cancer, 19 with lung cancer, 18 with colorectal cancer, 9 with renal cell cancer, 9 with prostate cancer), 39 family caregivers, and 20 health care professionals. Patients interviewed were being treated at the University of Texas M. D. Anderson Cancer Center or at the Hospice at the Texas Medical Center in Houston. In Phase II, 120 patients (30 with breast cancer, 30 with lung cancer, 30 with colorectal cancer, 15 with prostate cancer, and 15 with renal cell cancer) rated the importance of these concerns for quality of life. Items retained for the subscale were rated as "extremely important" or "very important" by at least 60% of the sample and were reported as being applicable by at least two-thirds of the sample. The 61 concerns that were identified were formatted as a questionnaire for Phase III. In Phase III, 356 patients (89 with breast cancer, 88 with lung cancer, 88 with colorectal cancer, 44 with prostate cancer, and 47 with renal cell cancer) were interviewed to determine the subscale's reliability and sensitivity to change in clinical status. Both factor analysis and item response theory supported the inclusion of the same 35 items for the subscale. Internal consistency reliability was moderate to high for the subscale's domains: spiritual (0.87), existential (0.76), medical care (0.68), symptoms (0.67), social/family (0.66), and emotional (0.61). Test-retest correlation coefficients also were high for the domains: social/family (0.86), emotional (0.83), medical care (0.83), spiritual (0.75), existential (0.75), and symptoms (0.81).^ In addition, concurrent validity was supported by the high correlation between the subscale's symptom domain and symptom items from the European Organization for Research and Treatment of Cancer (EORTC) scale (r = 0.74). Patients' functional status was assessed with the Eastern Cooperative Oncology Group (ECOG) Performance status rating. When ECOG categories were compared to subscale domains, patients who scored lower in functional status had lower scores in the spiritual, existential, social/family, and emotional domains. Patients who scored lower in physical well-being had higher scores in the symptom domain. Patient scores in the medical care domain were similar for each ECOG category. The results of this study support the subscale's use in assessing quality of life and the outcomes of palliative treatment for cancer patients in their last six months of life. ^

Micro RNA expression alterations in patients with glioblastoma

Glioblastoma, also known as glioblastoma multiform or GBM, is the most common and most malignant primary brain tumor. The clinical history of patients with glioblastoma is short, usually less than 3 months in more than 50% of cases after diagnosis. Currently, the methods of glioblastoma treatment are chemotherapy, radiotherapy and surgery. Even with the more effective treatment options, patients with glioblastoma most likely have a median survival time of 10 to 12 months. It is necessary to seek other treatment methods, including gene-targeted treatment. The success of gene-targeted treatment depends critically on the knowledge of genes that may be the cause of, or contribute to disease. To establish a correlate between glioblastoma survival timeline and micro RNA expression alteration, a study of 91 glioblastoma patients was conducted at the University of Texas M. D. Anderson Cancer Center. These 91 glioblastoma patients were newly diagnosed from 2002 to 2007. Statistical analysis was conducted to test the association of miRNA expression alteration between long-term survival and short-term survival glioblastoma. The completion of this proposed study will provide a better understanding of the regulatory role of miRNA in glioblastoma progression.^

Procedure for the identification of population characteristics for targeting intervention services on the basis of outcome-goal priorities: Case management services for the chronic mentally ill

Although the processes involved in rational patient targeting may be obvious for certain services, for others, both the appropriate sub-populations to receive services and the procedures to be used for their identification may be unclear. This project was designed to address several research questions which arise in the attempt to deliver appropriate services to specific populations. The related difficulties are particularly evident for those interventions about which findings regarding effectiveness are conflicting. When an intervention clearly is not beneficial (or is dangerous) to a large, diverse population, consensus regarding withholding the intervention from dissemination can easily be reached. When findings are ambiguous, however, conclusions may be impossible.^ When characteristics of patients likely to benefit from an intervention are not obvious, and when the intervention is not significantly invasive or dangerous, the strategy proposed herein may be used to identify specific characteristics of sub-populations which may benefit from the intervention. The identification of these populations may be used both in further informing decisions regarding distribution of the intervention and for purposes of planning implementation of the intervention by identifying specific target populations for service delivery.^ This project explores a method for identifying such sub-populations through the use of related datasets generated from clinical trials conducted to test the effectiveness of an intervention. The method is specified in detail and tested using the example intervention of case management for outpatient treatment of populations with chronic mental illness. These analyses were applied in order to identify any characteristics which distinguish specific sub-populations who are more likely to benefit from case management service, despite conflicting findings regarding its effectiveness for the aggregate population, as reported in the body of related research. However, in addition to a limited set of characteristics associated with benefit, the findings generated, a larger set of characteristics of patients likely to experience greater improvement without intervention. ^