Hospital healthcare resource utilization and costs for chimeric antigen T-cell therapy and autologous hematopoietic cell transplant in patients with large B-cell lymphoma in the United States.

The efficacy of chimeric antigen receptor (CAR) T-cell therapy for large B-cell lymphoma (LBCL) is well-established. This study, using the Premier PINC AI Healthcare Database, assessed hospital costs and healthcare resource utilization (HRU) between CAR T-cell therapy and autologous hematopoietic cell transplant (AHCT) for 733 LBCL patients from 01/01/2017-04/30/2021 (166 CAR T and 567 AHCT from 37 US hospital systems. CAR T-cell therapy had higher index costs but lower non-pharmacy costs, shorter hospital stays, lower ICU utilization than AHCT. The CAR T-cell cohort also presented fewer preparatory costs and HRU. At a 180-day follow-up, AHCT had lower hospitalization rates and costs. Overall, despite higher index costs, CAR T-cell therapy has lower non-pharmacy costs and HRU during the index procedure and requires less preparation time with lower preparation HRUs and costs than AHCT. This has important implications for resource management and informed decision-making for stakeholders.

Risk and promotive factors in families, schools, and communities: a contextual model of positive youth development in adolescence.

OBJECTIVE: Emerging evidence about optimal youth development highlights the importance of both reducing negative behavior and promoting positive behavior. In our study we tested a contextual model derived from positive youth-development theory by examining the association of family, school, and community risk and promotive factors, with several outcome indices of both positive and negative adolescent development. METHODS: A sample of 42305 adolescents aged 11 to 17 (51% girls) was drawn from the 2003 National Survey of Children's Health. Survey item composites were formed representing promotive and risk factors in the family (eg, closeness, aggression) and school and community (eg, community connectedness, school violence). Outcome composites reflected positive (social competence, health-promoting behavior, self-esteem) and negative (externalizing, internalizing, academic problems) developmental outcomes. Ordinary least squares regression was used to test the overall model. RESULTS: Between 0.10 and 0.50 of the variance in each outcome was explained by the contextual model. Multiple positive family characteristics were related to adolescent social competence and self-esteem, as well as lowered levels of internalizing and externalizing behavior and academic problems. Family communication, rules about television, and parents' own healthy behavior were related to adolescent health-promoting behavior. School and community safety were associated with increased social competence and decreased externalizing behavior. School violence was related to adolescent internalizing and externalizing behavior, as well as academic problems and lower self-esteem. CONCLUSIONS: Our results support the proposition that healthy adolescent development has roots in multiple contexts. Youth who were involved in contexts that provided positive resources from important others (ie, parents, schools, and communities) not only were less likely to exhibit negative outcomes, but also were more likely to show evidence of positive development. These findings provide important implications for intervention and prevention efforts and, more generally, for the promotion of positive, competent, and healthy youth development.

The impact of community risks and resources on adolescent risky behavior and health care expenditures.

PURPOSE: To examine a nested model that predicts adolescent risky behavior, health care use, and health care expenditures from individual characteristics, such as age and gender, and community characteristics such as social capital and community-level risky behavior rates. METHODS: Claims and encounter data were used to classify adolescents enrolled in Florida's Healthy Kids Program into two groups: those who engaged in risky behavior (ARB) and those who did not (NRB). Hierarchical linear modeling techniques were used to predict the odds of risky behavior, the odds of health care use, and health care expenditures based on individual and community characteristics. RESULTS: ARB consumed significantly more health care services than NRB, and their higher use and charges were attributable not only to individual level factors (i.e., age, gender, presence of special health care need, metropolitan residence status), but also to community level factors (i.e., social capital, risky behavior rates, violence, and ethnic/racial composition) as well. In particular, community investment in social capital predicted lower levels of risky behavior as well as lower health care expenditures. CONCLUSIONS: This information is important in terms of policy efforts at providing health care for this vulnerable group of individuals, as well as in developing prevention and intervention programs that can be delivered through the health care system and via links to community supports.