Using a theoretical approach to predict college students' non-medical use of prescription drugs - a survival analysis.

OBJECTIVES: This study assesses students' non-medical use of prescription drugs (NMUPD) from college entrance to graduation, and examines factors that predict NMUPD. Participants: The study was conducted between May 2011 and September 2015 with 338 students. Methods: Longitudinal cohort study design was used to examine NMUPD across time, and NMUPD-related attitudes and subjective norms. Five yearly interviews were conducted to collect data. Cox proportional hazards regression analysis was used to examine time to NMUPD. Results: Thirty-five percent of study participants reported NMUPD; the majority of those initiated non-medical use before their third year in college. Analyses indicated that more positive attitudes towards NMUPD (HR = 1.73, p < 0.001), increased subjective norms regarding NMUPD (HR = 1.01, p < 0.01), and gender (male) (HR= 1.89, p < 0.001) were significantly associated with sooner NMUPD. Conclusions: Findings suggest that NMUPD prevention efforts that target mutable factors such as attitudes and subjective norms should be implemented early during students' college careers.

A Model for Assessment of Catheterization Risk in Adults With Congenital Heart Disease.

The purpose of this study was to define the risk for adults with congenital heart disease who underwent cardiac catheterization and to propose a precatheterization risk scoring system. Data were prospectively collected using a multicenter registry of the Congenital Cardiovascular Interventional Study Consortium. The occurrence of serious adverse events (SAE) was correlated with 12 predefined variables. Catheterization RISk in Adult patients (CRISA) score was derived using multivariate logistic regression with backward elimination model selection method. The CRISA score was compared with the American Society of Anesthesiology score and a consensus-derived, 20-point risk score based on their ability to predict SAE. From June 2008 to September 2017, 300 adjudicated SAE's occurred in 7317 catheterization procedures (overall SAE rate 4.1%) performed in adults over 18 years of age at 27 contributing centers. Nine of the 12 tested variables were ultimately included in the CRISA score. CRISA score positively correlated with risk of SAE, and was superior to American Society of Anesthesiology and the 20-point risk score in predicting SAE. Minimal (CRISA score 0 to 2), low (3 to 7), moderate (8 to 10) and high (≥11) risk categories were identified, corresponding to 0.5%, 3.2%, 7.9%, and 16.7% risk of SAE, respectfully. In conclusion, the CRISA score reliably predicts risk of SAE in adults with congenital heart disease who underwent cardiac catheterization and may be useful for preprocedural risk assessment.

CRISP: Catheterization RISk score for Pediatrics: A Report from the Congenital Cardiac Interventional Study Consortium (CCISC).

OBJECTIVES: We sought to develop a scoring system that predicts the risk of serious adverse events (SAE's) for individual pediatric patients undergoing cardiac catheterization procedures. BACKGROUND: Systematic assessment of risk of SAE in pediatric catheterization can be challenging in view of a wide variation in procedure and patient complexity as well as rapidly evolving technology. METHODS: A 10 component scoring system was originally developed based on expert consensus and review of the existing literature. Data from an international multi-institutional catheterization registry (CCISC) between 2008 and 2013 were used to validate this scoring system. In addition we used multivariate methods to further refine the original risk score to improve its predictive power of SAE's. RESULTS: Univariate analysis confirmed the strong correlation of each of the 10 components of the original risk score with SAE attributed to a pediatric cardiac catheterization (P < 0.001 for all variables). Multivariate analysis resulted in a modified risk score (CRISP) that corresponds to an increase in value of area under a receiver operating characteristic curve (AUC) from 0.715 to 0.741. CONCLUSION: The CRISP score predicts risk of occurrence of an SAE for individual patients undergoing pediatric cardiac catheterization procedures.

CRISP: catheterization RISk score for pediatrics: a report from the congenital cardiac interventional study consortium (CCISC)

OBJECTIVES:We sought to develop a scoring system that predicts the risk of serious adverse events (SAE's) for individual pediatric patients undergoing cardiac catheterization procedures. BACKGROUND: Systematic assessment of risk of SAE in pediatric catheterization can be challenging in view of a wide variation in procedure and patient complexity as well as rapidly evolving technology. METHODS: A 10 component scoring system was originally developed based on expert consensus and review of the existing literature. Data from an international multi-institutional catheterization registry (CCISC) between 2008 and 2013 were used to validate this scoring system. In addition we used multivariate methods to further refine the original risk score to improve its predictive power of SAE's. RESULTS: Univariate analysis confirmed the strong correlation of each of the 10 components of the original risk score with SAE attributed to a pediatric cardiac catheterization (P < 0.001 for all variables). Multivariate analysis resulted in a modified risk score (CRISP) that corresponds to an increase in value of area under a receiver operating characteristic curve (AUC) from 0.715 to 0.741. CONCLUSION: The CRISP score predicts risk of occurrence of an SAE for individual patients undergoing pediatric cardiac catheterization procedures.

A phylogenetic model for understanding the effect of gene duplication on cancer progression.

As biotechnology advances rapidly, a tremendous amount of cancer genetic data has become available, providing an unprecedented opportunity for understanding the genetic mechanisms of cancer. To understand the effects of duplications and deletions on cancer progression, two genomes (normal and tumor) were sequenced from each of five stomach cancer patients in different stages (I, II, III and IV). We developed a phylogenetic model for analyzing stomach cancer data. The model assumes that duplication and deletion occur in accordance with a continuous time Markov Chain along the branches of a phylogenetic tree attached with five extended branches leading to the tumor genomes. Moreover, coalescence times of the phylogenetic tree follow a coalescence process. The simulation study suggests that the maximum likelihood approach can accurately estimate parameters in the phylogenetic model. The phylogenetic model was applied to the stomach cancer data. We found that the expected number of changes (duplication and deletion) per gene for the tumor genomes is significantly higher than that for the normal genomes. The goodness-of-fit test suggests that the phylogenetic model with constant duplication and deletion rates can adequately fit the duplication data for the normal genomes. The analysis found nine duplicated genes that are significantly associated with stomach cancer.

An algorithm to detect adverse drug reactions in the neonatal intensive care unit.

Critically ill newborns in neonatal intensive care units (NICUs) are at greater risk of developing adverse drug reactions (ADRs). Differentiation of ADRs from reactions associated with organ dysfunction/immaturity is difficult. Current ADR algorithm scoring was established arbitrarily without validation in infants. The study objective was to develop a valid and reliable algorithm to identify ADRs in the NICU. Algorithm development began with a 24-item questionnaire for data collection on 100 previously suspected ADRs. Five pediatric pharmacologists independently rated cases as definite, probable, possible, and unlikely ADRs. Consensus "gold standard" was reached via teleconference. Logistic regression and iterative C programs were used to derive the scoring system. For validation, 50 prospectively collected ADR cases were assessed by 3 clinicians using the new algorithm and the Naranjo algorithm. Weighted kappa and intraclass correlation coefficient (ICC) were used to compare validity and reliability of algorithms. The new algorithm consists of 13 items. Kappa and ICC of the new algorithm were 0.76 and 0.62 versus 0.31 and 0.43 for the Naranjo algorithm. The new algorithm developed using actual patient data is more valid and reliable than the Naranjo algorithm for identifying ADRs in the NICU population. Because of the relatively small and nonrandom samples, further refinement and additional testing are needed.

Potentially inappropriate medication use and healthcare expenditures in the US community-dwelling elderly.

BACKGROUND: Potentially inappropriate medication (PIM) use is a major source of drug-related problems in the elderly. Few studies have quantified the effect of PIM use on total healthcare expenditures in the United States. OBJECTIVES: : We sought to determine the relationship between PIM use and healthcare expenditure and to estimate the annual incremental healthcare expenditures related to PIM use in the community-dwelling elderly population in the United States in 2001. METHODS: This was a retrospective cohort study. Participants were age 65 years or older who had no PIM use in rounds 1 and 2 of the 2000-2001 Medical Expenditure Panel Survey, a nationally representative survey of the US noninstitutionalized population. On the basis of the 2002 Beers criteria, PIM users were identified as those who had been prescribed at least one PIM during specified time periods in the study. Propensity scores were used to match PIM users and nonusers in the analysis examining differences in total healthcare expenditures. RESULTS: PIM utilization is a significant predictor for higher healthcare expenditures (P < 0.05). A conservative estimate of the incremental healthcare expenditures related to PIM use in the community-dwelling elderly population would be $7.2 billion (95% confidence interval, $3.4 billion-$15.7 billion) in the United States in 2001. CONCLUSIONS: PIM use is a major patient safety concern that results in increased healthcare expenditures. This study emphasizes the need for continued provider education to inform prescribers of the potential risks of using certain medications in the elderly and to improve prescribing practices.

Off-label use of antidepressant, anticonvulsant, and antipsychotic medications among Georgia medicaid enrollees in 2001.

OBJECTIVES: To determine the prevalence of and factors associated with the off-label use of antidepressant, anticonvulsant, and antipsychotic medications. METHOD: A retrospective analysis of Georgia Medicaid recipients was conducted. Recipients prescribed antidepressant, anticonvulsant, or antipsychotic medications were identified. Logistic regression analysis was used to identify factors associated with off-label use. RESULTS: A total of 46,976 (75.42%) antidepressant recipients, 38,497 (80.12%) anticonvulsant recipients, and 21,252 (63.62%) antipsychotic recipients received at least 1 of these medications off-label in 2001. The likelihood of receiving off-label medications increased remarkably with advancing age (>or= 65 vs. < 65 years: antidepressant: OR = 5.15, 95% CI = 4.76 to 5.56; anticonvulsant: OR = 4.54, 95% CI = 4.16 to 4.96; antipsychotic: OR = 5.21, 95% CI = 4.82 to 5.63). Although receiving new anticonvulsants launched after 1993 was the strongest predictor (OR = 7.63, 95% CI = 7.07 to 8.23) of receiving off-label anticonvulsant medications, exposure to newer antidepressants and antipsychotics did not confer a higher chance of receiving off-label medications (selective serotonin reuptake inhibitors vs. tricyclic antidepressants: OR = 0.43, 95% CI = 0.40 to 0.45; atypical vs. conventional antipsychotics: OR = 0.76, 95% CI = 0.72 to 0.80). CONCLUSIONS: The off-label use of antidepressant, anticonvulsant, and antipsychotic medications is highly prevalent. Further research to study the effects of off-label use among this high risk subpopulation may be an important step toward defining the scope of and potential for such use.

Cost-effectiveness and lung cancer clinical trials.

BACKGROUND: Lung cancer is the leading cause of cancer death in the U.S., with an estimated annual economic burden of $5 billion. Clinical trials offer innovative therapeutic options with potentially better outcomes, but their effects on health care costs are disputed. METHODS: The authors analyzed the 1-year facility-based treatment cost and survival of 336 newly diagnosed nonsmall cell lung cancer patients who were deemed eligible for clinical trials between 1994 and 1998 at the Karmanos Cancer Institute. The incremental cost-effectiveness ratio (ICER) of clinical trial treatments with adjustment for confounders was calculated along with its 95% confidence interval (CI) using the bootstrap resampling method. RESULTS: Of the 336 patients, 76 (22.6%) were treated on clinical trials. Trial participation was associated significantly with race (P < 0.01), gender (P = 0.01), age (P = 0.02), and insurance type (P = 0.02). The average 1-year cost for trial enrollees was $41,734 with a median survival of 1.3 years, whereas the average 1-year cost for nonenrollees was $34,191 with a median survival period of 0.9 years. Differences in survival and 1-year cost between enrollees and nonenrollees were significant when controlling for age, race, gender, insurance, stage, performance status, and comorbidities. The ICER for trial participation after adjustment for confounders was $9741 per life year saved (95% CI, $3089-$19,149). CONCLUSIONS: Enrollment in lung cancer clinical trials was found to be associated with improved survival at a moderate incremental cost. Cancer 2003;98:1491-6.

On the meaning and measurement of nestedness of species assemblages.

Nestedness of species assemblages occurs when thebiotas of sites with lower numbers of species tend to be subsets of the biotas at richer sites. We develop new quantitative and statistical techniques for measuring, testing, and comparing nestedness, and apply these methods to data from the literature. Significantly nonrandom nestedness was present in all 27 assemblages examined, and tended to be stronger in systems dominated by extinction, such as landbridge islands. Sets of assemblages that were very strongly nested were more likely to have greater species richness on one or a few large sites than on several smaller sites of equivalent total area - that is, to fall toward the "single large" side of the "Single Large Or Several Small" (SLOSS) continuum. Our analysis indicates that nestedness, when quantified as a single number for a presence-absence matrix, measures community-wide differences in incidence (the frequency of occurrence or "distribution" of species). Factors that lead to consistent differences among species in immigration or extinction rates cause strong patterns of nestedness of species assemblages. Nestedness is negatively related to beta diversity: nestedness is low when beta diversity is high, and vice versa. Conservation managers will thus seek to minimize nestedness and the development of nested structure in systems of nature reserves.