KSU Chamber Singers and Men\u27s Ensemble

KSU School of Music presents Chamber Singers and Men\u27s Ensemble.https://digitalcommons.kennesaw.edu/musicprograms/1157/thumbnail.jp

KSU Men\u27s Ensemble, KSU Community & Alumni Choir and KSU Chamber Singers, Illumination

KSU School of Music presents Illumination with KSU Men\u27s Ensemble, The Kennesaw State University Community and Alumni Choir and KSU Chamber Singers featuring John Rutter\u27s Gloria!https://digitalcommons.kennesaw.edu/musicprograms/1249/thumbnail.jp

Ki67 Index, HER2 Status, and Prognosis of Patients With Luminal B Breast Cancer

"Background Gene expression profiling of breast cancer has identified two biologically distinct estrogen receptor (ER)-positive subtypes of breast cancer: luminal A and luminal B. Luminal B tumors have higher proliferation and poorer prognosis than luminal A tumors. In this study, we developed a clinically practical immunohistochemistry assay to distinguish luminal B from luminal A tumors and investigated its ability to separate tumors according to breast cancer recurrence-free and disease-specific survival. Methods Tumors from a cohort of 357 patients with invasive breast carcinomas were subtyped by gene expression profile. Hormone receptor status, HER2 status, and the Ki67 index (percentage of Ki67-positive cancer nuclei) were determined immunohistochemically. Receiver operating characteristic curves were used to determine the Ki67 cut point to distinguish luminal B from luminal A tumors. The prognostic value of the immunohistochemical assignment for breast cancer recurrence-free and disease-specific survival was investigated with an independent tissue microarray series of 4046 breast cancers by use of Kaplan–Meier curves and multivariable Cox regression. Results Gene expression profiling classified 101 (28%) of the 357 tumors as luminal A and 69 (19%) as luminal B. The best Ki67 index cut point to distinguish luminal B from luminal A tumors was 13.25%. In an independent cohort of 4046 patients with breast cancer, 2847 had hormone receptor–positive tumors. When HER2 immunohistochemistry and the Ki67 index were used to subtype these 2847 tumors, we classified 1530 (59%, 95% confidence interval [CI] = 57% to 61%) as luminal A, 846 (33%, 95% CI = 31% to 34%) as luminal B, and 222 (9%, 95% CI = 7% to 10%) as luminal–HER2 positive. Luminal B and luminal–HER2-positive breast cancers were statistically significantly associated with poor breast cancer recurrence-free and disease-specific survival in all adjuvant systemic treatment categories. Of particular relevance are women who received tamoxifen as their sole adjuvant systemic therapy, among whom the 10-year breast cancer–specific survival was 79% (95% CI = 76% to 83%) for luminal A, 64% (95% CI = 59% to 70%) for luminal B, and 57% (95% CI = 47% to 69%) for luminal–HER2 subtypes. Conclusion Expression of ER, progesterone receptor, and HER2 proteins and the Ki67 index appear to distinguish luminal A from luminal B breast cancer subtypes.

Predicting Suicides After Psychiatric Hospitalization in US Army Soldiers

IMPORTANCE: The US Army experienced a sharp increase in soldier suicides beginning in 2004. Administrative data reveal that among those at highest risk are soldiers in the 12 months after inpatient treatment of a psychiatric disorder. OBJECTIVE: To develop an actuarial risk algorithm predicting suicide in the 12 months after US Army soldier inpatient treatment of a psychiatric disorder to target expanded posthospitalization care. DESIGN, SETTING, AND PARTICIPANTS: There were 53,769 hospitalizations of active duty soldiers from January 1, 2004, through December 31, 2009, with International Classification of Diseases, Ninth Revision, Clinical Modification psychiatric admission diagnoses. Administrative data available before hospital discharge abstracted from a wide range of data systems (sociodemographic, US Army career, criminal justice, and medical or pharmacy) were used to predict suicides in the subsequent 12 months using machine learning methods (regression trees and penalized regressions) designed to evaluate cross-validated linear, nonlinear, and interactive predictive associations. MAIN OUTCOMES AND MEASURES: Suicides of soldiers hospitalized with psychiatric disorders in the 12 months after hospital discharge. RESULTS: Sixty-eight soldiers died by suicide within 12 months of hospital discharge (12.0% of all US Army suicides), equivalent to 263.9 suicides per 100,000 person-years compared with 18.5 suicides per 100,000 person-years in the total US Army. The strongest predictors included sociodemographics (male sex [odds ratio (OR), 7.9; 95% CI, 1.9-32.6] and late age of enlistment [OR, 1.9; 95% CI, 1.0-3.5]), criminal offenses (verbal violence [OR, 2.2; 95% CI, 1.2-4.0] and weapons possession [OR, 5.6; 95% CI, 1.7-18.3]), prior suicidality [OR, 2.9; 95% CI, 1.7-4.9], aspects of prior psychiatric inpatient and outpatient treatment (eg, number of antidepressant prescriptions filled in the past 12 months [OR, 1.3; 95% CI, 1.1-1.7]), and disorders diagnosed during the focal hospitalizations (eg, nonaffective psychosis [OR, 2.9; 95% CI, 1.2-7.0]). A total of 52.9% of posthospitalization suicides occurred after the 5% of hospitalizations with highest predicted suicide risk (3824.1 suicides per 100,000 person-years). These highest-risk hospitalizations also accounted for significantly elevated proportions of several other adverse posthospitalization outcomes (unintentional injury deaths, suicide attempts, and subsequent hospitalizations). CONCLUSIONS AND RELEVANCE: The high concentration of risk of suicide and other adverse outcomes might justify targeting expanded posthospitalization interventions to soldiers classified as having highest posthospitalization suicide risk, although final determination requires careful consideration of intervention costs, comparative effectiveness, and possible adverse effects

Predicting suicides after psychiatric hospitalization in US army soldiers:The Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

IMPORTANCE: The U.S. Army experienced a sharp rise in suicides beginning in 2004. Administrative data show that among those at highest risk are soldiers in the 12 months after inpatient treatment of a psychiatric disorder. OBJECTIVE: To develop an actuarial risk algorithm predicting suicide in the 12 months after US Army soldier inpatient treatment of a psychiatric disorder to target expanded post-hospital care. DESIGN, SETTING, AND PARTICIPANTS: There were 53,769 hospitalizations of active duty soldiers in 2004–2009 with ICD-9-CM psychiatric admission diagnoses. Administrative data available prior to hospital discharge abstracted from a wide range of data systems (socio81 demographic, Army career, criminal justice, medical/pharmacy) were used to predict suicides in the subsequent 12 months using machine learning methods (regression trees, penalized regressions) designed to evaluate cross-validated linear, nonlinear, and interactive predictive associations. MAIN OUTCOME: Suicides of soldiers hospitalized with psychiatric disorders in the 12 months after hospital discharge. RESULTS: 68 soldiers died by suicide within 12 months of hospital discharge (12.0% of all Army suicides), equivalent to 263.9 suicides/100,000 person-years compared to 18.5 suicides/100,000 person-years in the total Army. Strongest predictors included socio-demographics (male, late age of enlistment), criminal offenses (verbal violence, weapons possession), prior suicidality, aspects of prior psychiatric inpatient and outpatient treatment, and disorders diagnosed during the focal hospitalizations. 52.9% of post-hospital suicides occurred after the 5% of hospitalizations with highest predicted suicide risk (3,824.1 suicides/100,000 person years). These highest-risk hospitalizations also accounted for significantly elevated proportions of several other adverse post-hospital outcomes (unintentional injury deaths, suicide attempts, re-hospitalizations). CONCLUSIONS AND RELEVANCE: The high concentration of risk of suicides and other adverse outcomes might justify targeting expanded post-hospital interventions to soldiers classified as having highest post-hospital suicide risk, although final determination requires careful consideration of intervention costs, comparative effectiveness, and possible adverse effects

Medical Residents' First Clearly Remembered Experiences of Giving Bad News

CONTEXT: Communication of bad news to patients or families is a difficult task that requires skill and sensitivity. Little is known about doctors' formative experiences in giving bad news, what guidance they receive, or what lessons they learn in the process. OBJECTIVE: To learn the circumstances in which medical residents first delivered bad news to patients or families, the nature of their experience, and their opinions about how best to develop the needed skills. DESIGN: Confidential mailed survey. SETTING AND SUBJECTS: All medicine house officers at 2 urban, university-based residency programs in Boston. MAIN OUTCOME MEASURES: Details of medical residents' first clearly remembered experiences of giving bad news to a patient or family member; year in training; familiarity with the patient; information about any planning prior to, observation of, or discussion after their first experience; and the usefulness of such discussions. We also asked general questions about delivering bad news, such as how often this was done, as well as asking for opinions about actual and desired training. RESULTS: One hundred twenty-nine of two hundred thirteen surveys (61%) were returned. Most (73%) trainees first delivered bad news while a medical student or intern. For this first experience, most (61%) knew the patient for just hours or days. Only 59% engaged in any planning for the encounter. An attending physician was present in 6 (5%) instances, and a more-senior trainee in 14 (11%) others. Sixty-five percent of subjects debriefed with at least 1 other person after the encounter, frequently with a lesser-trained physician or a member of their own family. Debriefing focused on the reaction of those who were given the bad news and the reaction of the trainee. When there were discussions with more-senior physicians, before or after the encounter, these were judged to be helpful approximately 80% of the time. Most subjects had given bad news between 5 and 20 times, yet 10% had never been observed doing so. Only 81 of 128 (63%) had ever observed an attending delivering bad news, but those who did found it helpful 96% of the time. On 7-point scales, subjects rated the importance of skills in delivering bad news highly, (mean 6.8), believed such skill can be improved (mean 6.6), and thought that more guidance should be offered to them during such activity (mean 5.8). CONCLUSION: Medical students and residents frequently deliver bad news to patients and families. This responsibility begins early in training. In spite of their inexperience, many do not appear to receive adequate guidance or support during their earliest formative experiences