SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

Physical activity and survival after a first myocardial infarction: The Corpus Christi Heart Project

Previous studies have demonstrated that habitual physical activity is associated with a reduced risk of incident coronary heart disease (CHD). However, the role of physical activity in lowering the risk of all-cause mortality, CHD mortality, reinfarction, or receipt of a revascularization procedure after a first myocardial infarction (MI) remains unresolved, particularly in minority populations. To investigate the associations between physical activity and risk of all-cause mortality, CHD mortality, reinfarction, and receipt of a revascularization procedure, this study was conducted among Mexican-American and non-Hispanic white women and men who survived a first MI. The Corpus Christi Heart Project, a population-based cardiovascular surveillance study, provide data which included vital status, survival time, medical history, CHD risk factor information, including level of physical activity among Mexican-American and non-Hispanic white adults who had experienced a first MI between May, 1988 and April, 1990. MI patients were interviewed at baseline and annually thereafter until their death or through May, 1995. A categorical variable was created to reflect change in level of physical activity following the first MI; categories included (1) sedentary with no change, (2) decreased activity, (3) increased activity, and (4) moderate activity with no change (the referent group). Proportional hazards regression analyses were used to assess the relationship of level of physical activity and risk of death, reinfarction, or receipt of a revascularization procedure adjusting for age, sex, ethnicity, severity of MI, and CHD risk factor status. Over a 7-year follow-up period, the relative risk (95% confidence intervals) of all-cause mortality was 4.67 (2.27, 9.60) for the sedentary-no change group, 2.33 (0.96, 5.67) for the decreased activity group, and 0.52 (0.11, 2.41) for the increased activity group. The relative risk of CHD mortality was 6.92 (2.05, 23.34) for the sedentary-no change group, 2.40 (0.55, 10.51) for the decreased activity group, and 1.58 (0.26, 9.65) for the increased activity group. The relative risk for reinfarction was 2.50 (1.52, 4.10) for the sedentary-no change group, 2.26 (1.24, 4.12) for the decreased activity group, and 0.52 (0.21, 1.32) for the increased activity group. Finally, the relative risk for receipt of a revascularization procedure was 0.65 (0.39, 1.07) for the sedentary-no change group, 0.45 (0.22, 0.92) for the decreased activity group, and 1.01 (0.51, 2.02) for the increased activity group. No interactions were observed for ethnicity or severity of first MI. These results are consistent with the hypothesis that moderate physical activity is independently associated with a lower risk of all-cause mortality, CHD mortality, and reinfarction, but not revascularization, among Mexican-American and non-Hispanic white, female and male, first MI patients. These results also support the current recommendation that physical activity plays an important role in the secondary prevention of CHD. ^

Simulation study of joint transition and Weibull survival model with shared parameters

This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^

The role of cardiovascular comorbidities in ovarian cancer survival

Objective. One facet of cancer care that often goes ignored is comorbidities, or diseases that exist in concert with cancer. Comorbid conditions may affect survival by influencing treatment decisions and prognosis. The purpose of this secondary data analysis was to identify whether a history of cardiovascular comorbidities among ovarian cancer patients influenced survival time at the University of Texas M. D. Anderson Cancer Center. The parent study, Project Peace, has a longitudinal design with an embedded randomized efficacy study which seeks to improve detection of depressive disorders in ovarian, peritoneal, and fallopian tube cancers. ^ Methods. Survival time was calculated for the 249 ovarian cancer patients abstracted by Project Peace staff. Cardiovascular comorbidities were documented as present, based upon information from medical records in addition to self reported comorbidities in a baseline study questionnaire. Kaplan-Meier survival curves were used to compare survival time among patients with a presence or absence of particular cardiovascular comorbidities. Cox Regression proportional models accounted for multivariable factors such as age, staging, family history of cardiovascular comorbidities, and treatment. ^ Results. Among our patient population, there was a statistically significant relationship between shorter survival time and a history of thrombosis, pericardial disease/tamponade, or COPD/pulmonary hypertension. Ovarian cancer patients with a history of thrombosis lived approximately half as long as patients without thrombosis (58.06 months vs. 121.55 months; p=.001). In addition, patients who suffered from pericardial disease/tamponade had poorer survival than those without a history of pericardial disease/tamponade (48 months vs. 80.07 months; p=.002). Ovarian cancer patients with a history of COPD or pulmonary hypertension had a median survival of 60.2 months, while the median survival for patients without these comorbidities was 80.2 months (p=.014). ^ Conclusion. Especially because of its relatively lower survival rate, greater emphasis needs to be placed on the potential influence of cardiovascular comorbid conditions in ovarian cancer.^

Prognostic significance of xCT polymorphisms and expression in patients with advanced pancreatic cancer treated with chemotherapy

The plasma membrane xc- cystine/glutamate transporter mediates cellular uptake of cystine in exchange for intracellular glutamate and is highly expressed by pancreatic cancer cells. The xCT gene, encoding the cystine-specific xCT protein subunit of xc-, is important in regulating intracellular glutathione (GSH) levels, critical for cancer cell protection against oxidative stress, tumor growth and resistance to chemotherapeutic agents including platinum. We examined 4 single nucleotide polymorphisms (SNPs) of the xCT gene in 269 advanced pancreatic cancer patients who received first line gemcitabine with or without cisplatin or oxaliplatin. Genotyping was performed using Taqman real-time PCR assays. A statistically significant correlation was noted between the 3' untranslated region (UTR) xCT SNP rs7674870 and overall survival (OS): Median survival time (MST) was 10.9 and 13.6 months, respectively, for the TT and TC/CC genotypes (p = 0.027). Stratified analysis showed the genotype effect was significant in patients receiving gemcitabine in combination with platinum therapy (n = 145): MST was 10.5 versus 14.1 months for the TT and TC/CC genotypes, respectively (p = 0.013). The 3' UTR xCT SNP rs7674870 may correlate with OS in pancreatic cancer patients receiving gemcitabine and platinum combination therapy. Paraffin-embedded core and surgical biopsy tumor specimens from 98 patients with metastatic pancreatic adenocarcinoma were analyzed by immunohistochemistry using an xCT specific antibody. xCT protein IHC expression scores were analyzed in relation to overall survival in 86 patients and genotype in 12 patients and no statistically significant association was found between the level of xCT IHC expression score and overall survival (p = 0.514). When xCT expression was analyzed in terms of treatment response, no statistically significant associations could be determined (p = 0.908). These data suggest that polymorphic variants of xCT may have predictive value, and that the xc- transporter may represent an important target for therapy in pancreatic cancer.

The prognostic significance of sialyl-Tn antigen in women treated with adjuvant chemotherapy for breast cancer

Background and purpose. Sialyl-Tn(STn) represents an aberrantly glycosylated mucin epitope which is expressed in breast cancer and other adenocarcinomas and is an important target for the development of novel immunotherapeutic approaches. It is a marker of adverse prognosis in colon and ovarian cancer, but information about its prognostic impact in breast cancer is limited. The primary aim of the present study was to investigate the influence of STn expression on outcome of invasive breast cancer in 207 women who received anthracyline-containing adjuvant chemotherapy in a prospective clinical trial.^ Methods. Expression of STn was determined by an immunohistochemical procedure using the B72.3 monoclonal antibody. The extent of staining was determined by two observers using a 0 through 4 point scale, with 0 representing $<$5% of cells staining; 1: 5-25%; 2: 26-50%; 3: 51-75%; and 4: $>$75%. Intraobserver and interobserver agreement was.78-.92 (kappa). Kaplan-Meier and Cox proportional regression survival analyses were used to compare STn-negative and STn-positive patients.^ Results. Forty-eight (23%) of the 207 specimens demonstrated positive staining of STn. With a median follow-up of five years, STn-positivity was associated with a higher 5-year recurrence-free survival time than STn-negativity (67% vs. 80%, respectively; p = 0.03). STn expression was significantly associated with menopausal status (p = 0.04) but not other conventional prognostic markers. The risk of breast cancer recurrence and death was assessed by multivariate Cox regression analyses with adjustment for lymph node status, tumor size, menopausal status, hormone receptor status, nuclear grade, S-phase fraction and ploidy. In the final multivariate model for recurrence-free survival, the three factors that showed prognostic significance were: lymph node status (hazard ratio (HR) 3.04, 95% confidence interval (CI) 1.08-8.49), STn expression (HR 2.02, 95% CI 1.09-3.73), and tumor size (HR 1.96, 95% CI 1.05-3.64). STn was also associated with worse overall survival (HR 2.16, 95% CI 0.95-4.92) in multivariate analysis.^ Conclusion. STn antigen was shown to be a predictor of poor outcome in breast cancer. This tumor-associated antigen may be a valuable marker for identifying individuals at high risk of developing recurrent disease who may benefit from adjuvant therapy targeted at STn following definitive local therapy. Further study is needed to clarify the biologic and prognostic role of STn in breast cancer. ^

Mechanisms of Ad-p53 induced apoptosis in human malignant glioma

Malignant brain tumors are one of the most challenging cancers affecting society today. In a recent survey, an estimated 17,000 annual cases were recorded with a staggering total of 13,300 deaths. A unique degree of heterogeneity typifies glial tumors and presents a challenge for solitary anti-neoplastic treatments. Tumors subsist as heterogeneous masses that progress through dysplasia to astrocytomas, mixed glioma and glioblastoma multiforme. Although traditional therapeutic approaches have provided increments of success, the median survival time remains 12 months. The urgency to improve upon current clinical protocols has encouraged alternative experimental strategies such as p53 adenoviral gene therapy (Ad-p53). This study addresses the efficacy of Ad-p53 for the treatment of glioma. Our model presents a tumor response that is unique among human cancers. Ad-p53 effectively induces apoptosis in mutant p53 expressing cells yet fails to do so in those with wildtype p53. In order to adopt Adp53 as a standard anti-cancer modality, we characterized the role of the tumor suppressor gene p53 in mediating apoptosis. We demonstrate that altering cellular p53 status through the introduction of a dominant negative mutant p53 (175H, 248W, 273H) sensitized cells to Ad-p53. We discovered that wild-type p53 expressing glioma cells retain the apoptotic machinery necessary to accomplish cell death, but have developed mechanisms that interfere with p53 signaling. Earlier studies have not addressed the mechanisms of Ad-p53 apoptosis nor the resistance exhibited by wild-type p53 glioma. To explain the divergent phenotypes, we identified apoptotic pathways activated and effectors of the response. We illustrated that modulation of the death receptor Fas/APO-1 is a principal means of Ad-p53 signaling that is impaired in wild-type p53 glioma. Moreover, the apoptotic response was found to be a multi-faceted process that engaged several caspases, most notably caspases -1, -3 and -8. Lastly, we assessed the ability of anti-apoptotic molecules Bcl-2 and CrmA to inhibit Ad-p53 apoptosis. These studies revealed that Ad-p53 is a powerful tool for inducing apoptosis that can be delayed but not inhibited by anti-apoptotic means. This work is critical for understanding the development of glioma and the phenotypic and genotypic alterations that account for tumor resistance. ^

Comparison of a traditional and a multilevel Cox Proportional Hazards model

Hierarchically clustered populations are often encountered in public health research, but the traditional methods used in analyzing this type of data are not always adequate. In the case of survival time data, more appropriate methods have only begun to surface in the last couple of decades. Such methods include multilevel statistical techniques which, although more complicated to implement than traditional methods, are more appropriate. ^ One population that is known to exhibit a hierarchical structure is that of patients who utilize the health care system of the Department of Veterans Affairs where patients are grouped not only by hospital, but also by geographic network (VISN). This project analyzes survival time data sets housed at the Houston Veterans Affairs Medical Center Research Department using two different Cox Proportional Hazards regression models, a traditional model and a multilevel model. VISNs that exhibit significantly higher or lower survival rates than the rest are identified separately for each model. ^ In this particular case, although there are differences in the results of the two models, it is not enough to warrant using the more complex multilevel technique. This is shown by the small estimates of variance associated with levels two and three in the multilevel Cox analysis. Much of the differences that are exhibited in identification of VISNs with high or low survival rates is attributable to computer hardware difficulties rather than to any significant improvements in the model. ^

A meta-analysis: Obesity and colorectal cancer screening

Of cancer death, colorectal cancer death ranks second in the United States. Obesity is an important risk factor for colorectal cancer (1). Early detection of colorectal cancer when it is localized can effectively reduce mortality of colorectal cancer and increase survival time of patients if they are treated. Also, previous studies showed that obese women were more likely to delay breast cancer screening and cervical cancer screening than normal weight women (2-5). However, results from prior studies demonstrating the relationship between obesity and colorectal cancer screening are not consistent. This research was done to conduct a meta-analysis of previous cross-sectional studies selected from the Medline database and to evaluate the association between obesity and colorectal cancer screening. While the odds ratio was not statistically different from one, the results from this meta-analysis under the random effects model showed that obese people are slightly less likely to have colorectal cancer screening compared to normal weight individuals (OR,0.93;95% CI 0.75-1.15). This meta-analysis was particularly sensitive to one individual study (6) and the effect of obesity on colorectal cancer screening was statistically significant (OR, 0.87; 95% CI, 0.81-0.92) after removing Heo's study. Further systematic studies focused on whether the effect of obesity on colorectal cancer screening is limited to women only are suggested. ^

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.^

Comparison of medical care costs, utilization, and satisfaction of AIDS patients with and without home care

A sample of 157 AIDS patients 17 years of age or over were followed for six months from the date of hospital discharge to derive average total cost of medical care, utilization and satisfaction with care. Those referred for home care follow-up after discharge from the hospital were compared with those who did not receive home care.^ The average total cost of medical care for all patients was $34,984. Home care patient costs averaged \$29,614 while patients with no home care averaged $37,091. Private hospital patients had average costs of \$50,650 compared with $25,494 for public hospital patients. Hospital days for the six months period averaged 23.9 per patient for the no home care group and 18.5 days for home care group. Patient satisfaction with care was higher in the home care group than no home care group, with a mean score of 68.2 compared with 61.1.^ Other health services information indicated that 98% of the private hospital patients had insurance while only 2% of public hospital patients had coverage. The time between the initial date of diagnosis with AIDS and admission to the study was longer for private hospital patients, survival time over the study period was shorter, and the number of hospitalizations prior to entering the study was higher for private hospital patients. These results suggest that patients treated in the private hospital were sicker than public hospital patients, which may explain their higher average total cost. Statistical analyses showed that cost and utilization have no significant relationship with home care or no home care when controlling for indicators of the severity of illness and treatment in public or private hospital.^ In future studies, selecting a matched group of patients from the same hospital and following them for nine months to one year would be helpful in making a more realistic comparison of the cost effectiveness of home care. ^

Data quality in trauma transfusion studies and the impact of missing data on predicting massive transfusion

Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^

Developing the follow-up schedules for women with breast cancer

Background: The follow-up care for women with breast cancer requires an understanding of disease recurrence patterns and the follow-up visit schedule should be determined according to the times when the recurrence are most likely to occur, so that preventive measure can be taken to avoid or minimize the recurrence. Objective: To model breast cancer recurrence through stochastic process with an aim to generate a hazard function for determining a follow-up schedule. Methods: We modeled the process of disease progression as the time transformed Weiner process and the first-hitting-time was used as an approximation of the true failure time. The women's "recurrence-free survival time" or a "not having the recurrence event" is modeled by the time it takes Weiner process to cross a threshold value which represents a woman experiences breast cancer recurrence event. We explored threshold regression model which takes account of covariates that contributed to the prognosis of breast cancer following development of the first-hitting time model. Using real data from SEER-Medicare, we proposed models of follow-up visits schedule on the basis of constant probability of disease recurrence between consecutive visits. Results: We demonstrated that the threshold regression based on first-hitting-time modeling approach can provide useful predictive information about breast cancer recurrence. Our results suggest the surveillance and follow-up schedule can be determined for women based on their prognostic factors such as tumor stage and others. Women with early stage of disease may be seen less frequently for follow-up visits than those women with locally advanced stages. Our results from SEER-Medicare data support the idea of risk-controlled follow-up strategies for groups of women. Conclusion: The methodology we proposed in this study allows one to determine individual follow-up scheduling based on a parametric hazard function that incorporates known prognostic factors.^

Comparison of clinical and economic outcomes between high-intensity care and hospice care for the end-of-life melanoma patients

The intensity of care for patients at the end-of-life is increasing in recent years. Publications have focused on intensity of care for many cancers, but none on melanoma patients. Substantial gaps exist in knowledge about intensive care and its alternative, hospice care, among the advanced melanoma patients at the end of life. End-of-life care may be used in quite different patterns and induce both intended and unintended clinical and economic consequences. We used the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked databases to identify patients aged 65 years or older with metastatic melanoma who died between 2000 and 2007. We evaluated trends and associations between sociodemographic and health services characteristics and the use of hospice care, chemotherapy, surgery, and radiation therapy and costs. Survival, end-of-life costs, and incremental cost-effectiveness ratio were evaluated using propensity score methods. Costs were analyzed from the perspective of Medicare in 2009 dollars. In the first journal Article we found increasing use of surgery for patients with metastatic melanoma from 13% in 2000 to 30% in 2007 (P=0.03 for trend), no significant fluctuation in use of chemotherapy (P=0.43) or radiation therapy (P=0.46). Older patients were less likely to receive radiation therapy or chemotherapy. The use of hospice care increased from 61% in 2000 to 79% in 2007 (P =0.07 for trend). Enrollment in short-term (1-3 days) hospice care use increased, while long-term hospice care (≥ 4 days) remained stable. Patients living in the SEER Northeast and South regions were less likely to undergo surgery. Patients enrolled in long-term hospice care used significantly less chemotherapy, surgery and radiation therapy. In the second journal article, of 611 patients identified for this study, 358 (59%) received no hospice care after their diagnosis, 168 (27%) received 1 to 3 days of hospice care, and 85 (14%) received 4 or more days of hospice care. The median survival time was 181 days for patients with no hospice care, 196 days for patients enrolled in hospice for 1 to 3 days, and 300 days for patients enrolled for 4 or more days (log-rank test, P < 0.001). The estimated hazard ratios (HR) between 4 or more days hospice use and survival were similar within the original cohort Cox proportional hazard model (HR, 0.62; 95% CI, 0.49-0.78, P < 0.0001) and the propensity score-matched model (HR, 0.61; 95% CI, 0.47-0.78, P = 0.0001). Patients with ≥ 4 days of hospice care incurred lower end-of-life costs than the other two groups ($14,298 versus $19,380 for the 1- to 3-days hospice care, and $24,351 for patients with no hospice care; p < 0.0001). In conclusion, Surgery and hospice care use increased over the years of this study while the use of chemotherapy and radiation therapy remained consistent for patients diagnosed with metastatic melanoma. Patients diagnosed with advanced melanoma who enrolled in ≥ 4 days of hospice care experienced longer survival than those who had 1-3 days of hospice or no hospice care, and this longer overall survival was accompanied by lower end-of-life costs.^

Runaway and Throwaway Youth: Time for Policy Changes and Public Responsibility

The traditional American dream of owning a home, obtaining a college education, and working at a good, paying job is only that, a dream, for scores of homeless youth in America today. There is a growing street population of young people who have been thrown out of their homes by their caretakers or their families, and who face life-threatening situations each day. For these youth, the furthest thing in their lives is reaching the so-called “American Dream;” and their most immediate need is survival, simply living out the day in front of them. They have few options that lead to a decent and safe living environment. Their age, lack of work experience, and absence of a high school diploma make it most difficult to find a job. As a result, they turn to other means for survival; runaways and throwaways are most vulnerable to falling prey to the sex trade, selling drugs, or being lured into human trafficking, and some steal or panhandle. Street youth end up spending their nights in bus stations or finding a room in an abandoned building or an empty stairwell to sleep. Attempting to identify a specific number of homeless youth is difficult at best, but what is even more perplexing is our continued inability to effectively protect our children. We are left with a basic question framed by the fundamental tenets of justice: what is a community’s responsibility to its youth who, for whatever reason, end up living on the streets or in unsafe, abusive environments? The purpose of this paper is to briefly outline the characteristics of homeless youth, in particular differentiating between throwaways and runaways; explore the current federal response to homeless youth; and finally, address the nagging question that swirls around all children: can we aggressively aspire to be a community where every child is healthy and safe, and able to realize his or her fullest potential?