Phenobarbital and phenytoin are equally but incompletely effective as anticonvulsants in neonates. With either drug given alone, the seizures were controlled in fewer than half of the neonates.

For analyses of longitudinal repeated-measures data, statistical methods include the random effects model, fixed effects model and the method of generalized estimating equations. We examine the assumptions that underlie these approaches to assessing covariate effects on the mean of a continuous, dichotomous or count outcome. Access to statistical software to implement these models has led to widespread application in numerous disciplines. However, careful consideration should be paid to their critical assumptions to ascertain which model might be appropriate in a given setting. To illustrate similarities and differences that might exist in empirical results, we use a study that assessed depressive symptoms in low-income pregnant women using a structured instrument with up to five assessments that spanned the pre-natal and post-natal periods. Understanding the conceptual differences between the methods is important in their proper application even though empirically they might not differ substantively. The choice of model in specific applications would depend on the relevant questions being addressed, which in turn informs the type of design and data collection that would be relevant.

Objective Osteoarthritis (OA) is a chronic and slowly progressive disease for which biomarkers may be able to provide a more rapid indication of therapeutic responses to therapy than is currently available; this could accelerate and facilitate OA drug discovery and development programs. The goal of this document is to provide a summary and guide to the application of in vitro (biochemical and other soluble) biomarkers in the development of drugs for OA and to outline and stimulate a research agenda that will further this goal. Methods The Biomarkers Working Group representing experts in the field of OA biomarker research from both academia and industry developed this consensus document between 2007–2009 at the behest of the Osteoarthritis Research Society International (OARSI FDA initiative). Results This document summarizes definitions and classification systems for biomarkers, the current outcome measures used in OA clinical trials, applications and potential utility of biomarkers for development of OA therapeutics, the current state of qualification of OA-related biomarkers, pathways for biomarker qualification, critical needs to advance the use of biomarkers for drug development, recommendations regarding practices and clinical trials, and a research agenda to advance the science of OA-related biomarkers. Conclusions Although many OA-related biomarkers are currently available they exist in various states of qualification and validation. The biomarkers that are likely to have the earliest beneficial impact on clinical trials fall into two general categories, those that will allow targeting of subjects most likely to either respond and/or progress (prognostic value) within a reasonable and manageable time frame for a clinical study (for instance within one to two years for an OA trial), and those that provide early feedback for preclinical decision-making and for trial organizers that a drug is having the desired biochemical effect. As in vitro biomarkers are increasingly investigated in the context of specific drug treatments, advances in the field can be expected that will lead to rapid expansion of the list of available biomarkers with increasing understanding of the molecular processes that they represent.

The current national system for work-related injuries and illnesses markedly underestimates the magnitude of these conditions. A more comprehensive system, such as the one developed for traumatic workplace fatalities, that is not solely dependent on employer based data sources is needed to better guide decision-making and evaluation of public health programs to reduce work-related conditions.

OBJECTIVE: There is no proven primary care treatment for patients with medically unexplained symptoms (MUS). We hypothesized that a long‐term, multidimensional intervention by primary care providers would improve MUS patients' mental health. DESIGN: Clinical trial. SETTING: HMO in Lansing, MI. PARTICIPANTS: Patients from 18 to 65 years old with 2 consecutive years of high utilization were identified as having MUS by a reliable chart rating procedure; 206 subjects were randomized and 200 completed the study. INTERVENTION: From May 2000 to January 2003, 4 primary care clinicians deployed a 12‐month intervention consisting of cognitive–behavioral, pharmacological, and other treatment modalities. A behaviorally defined patient‐centered method was used by clinicians to facilitate this treatment and the provider‐patient relationship. MAIN OUTCOME MEASURE: The primary endpoint was an improvement from baseline to 12 months of 4 or more points on the Mental Component Summary of the SF‐36. RESULTS: Two hundred patients averaged 13.6 visits for the year preceding study. The average age was 47.7 years and 79.1% were females. Using intent to treat, 48 treatment and 34 control patients improved (odds ratio [OR]=1.92, 95% confidence interval [CI]: 1.08 to 3.40; P=.02). The relative benefit (relative “risk” for improving) was 1.47 (CI: 1.05 to 2.07), and the number needed to treat was 6.4 (95% CI: 0.89 to 11.89). The following baseline measures predicted improvement: severe mental dysfunction (P<.001), severe body pain (P=.039), nonsevere physical dysfunction (P=.003), and at least 16 years of education (P=.022); c‐statistic=0.75. CONCLUSION: The first multidimensional intervention by primary care clinicians led to clinically significant improvement in MUS patients.

Late-preterm birth is associated with behavioral problems and lower IQ at the age of 6, independent of maternal IQ, residential setting, and sociodemographics. Future research is needed to investigate whether these findings result from a reduction in gestational length, in utero (eg, obstetric complications) or ex-utero (eg, neonatal complications) factors marked by late-preterm birth, or some combination of these factors.

We found no association between PBB serum levels and diabetes incidence. In women, there was a positive linear association of diabetes incidence with PCB serum levels at enrollment. This finding is in agreement with 2 prior studies indicating a higher relative risk of diabetes in PCB-exposed women.

BACKGROUND The current article examined survival for adults < 65 years old diagnosed with breast, colorectal, or lung carcinoma who were either Medicaid insured at the time of diagnosis, Medicaid insured after diagnosis, or non‐Medicaid insured. METHODS The authors hypothesized that subjects enrolling in Medicaid after they were diagnosed with cancer would explain disparate survival outcomes between Medicaid and non–Medicaid‐insured subjects. The authors used the Michigan Tumor Registry, a population‐based cancer registry covering the State of Michigan, to identify subjects who were diagnosed with the cancer sites of interest (n = 13,740). The primary outcome was all cause mortality over an 8‐year time period. RESULTS Subjects who enrolled in Medicaid after diagnosis with cancer had much lower 8‐year survival rates relative to Medicaid‐enrolled and non‐Medicaid subjects. These reductions in survival were partly due to a high proportion of lung carcinoma and late‐stage cancers within the sample of subjects who enrolled in Medicaid after diagnosis. The likelihood of death was two to three times greater for subjects enrolled in Medicaid relative to subjects who were not enrolled in Medicaid once the analysis was stratified by cancer site and stage. CONCLUSIONS Disparities in cancer survival were apparent between subjects enrolled in Medicaid and subjects not enrolled in Medicaid. From a policy perspective, cancer survival in the Medicaid population cannot be improved as long as 40% of the population enrolls in Medicaid after diagnosis with late‐stage disease. Cancer 2005. © 2005 American Cancer Society.