A predicted operon map for Mycobacterium tuberculosis.

The prediction of operons in Mycobacterium tuberculosis (MTB) is a first step toward understanding the regulatory network of this pathogen. Here we apply a statistical model using logistic regression to predict operons in MTB. As predictors, our model incorporates intergenic distance and the correlation of gene expression calculated for adjacent gene pairs from over 474 microarray experiments with MTB RNA.

Optimal length of continuation therapy in depression: a prospective assessment during long-term fluoxetine treatment.

Objective: The purpose of this study was to determine prospectively the optimal length of therapy in a long-term, placebo-controlled continuation study of patients who responded to acute fluoxetine treatment for major depression (defined by DSM-III-R).

Method: The study was conducted at five outpatient psychiatric clinics in the United States. Patients who met criteria for remission after 12 or 14 weeks of open-label acute fluoxetine therapy, 20 mg/day (N=395 of 839 patients), were randomly assigned to one of four arms of a double-blind treatment study (50 weeks of placebo, 14 weeks of fluoxetine and then 36 weeks of placebo, 38 weeks of fluoxetine and then 12 weeks of placebo, or 50 weeks of fluoxetine).

Use of pattern analysis to predict differential relapse of remitted patients with major depression during 1 year of treatment with fluoxetine or placebo.

Background: Delayed and persistent ("true drug") improvement characterizes the response to antidepressant medication. Early or nonpersistent ("placebo") benefit is typical of a placebo response. The prediction was that patients with a true drug response would sustain their benefit best if they continued to receive the drug and that patients with a placebo response would have an equivalent prognosis whether they continued to receive the drug or were switched to placebo.

Efficacy and safety of long-term fluoxetine treatment of obesity--maximizing success.

Obesity is a major health care concern because of its associated medical complications and increased mortality. Despite a myriad of short-term weight loss strategies and the motivation of improving health, patients have difficulty maintaining reduced weight. Pharmacologic agents, such as fluoxetine, a selective serotonin uptake inhibitor, have been investigated as adjunctive therapy to standard weight management programs.

Acute effects of fluoxetine versus placebo on functional health and well-being in late-life depression.

In a randomized 6-week trial comparing fluoxetine with placebo, the Medical Outcomes Study 36-Item Short-Form Health Status Survey (SF-36) scales were used to measure the effects of treatment on functional health and well-being among elderly (age > or = 60 years) outpatients with major depression. In the fluoxetine and placebo groups, 261 and 271 patients, respectively, completed the SF-36 before treatment and at Weeks 3 and 6. Compared with national norms for individuals over age 60, study patients before treatment exhibited baseline decrements on the following SF-36 scales: mental health, role limitations due to emotional problems, social functioning, vitality, role limitations due to physical problems, and bodily pain.

Evaluating success of weight loss programs, with an application to fluoxetine weight reduction clinical trial data.

We modified criteria for judging successful obesity treatment proposed by Atkinson to provide objective criteria for successful benefit from weight reduction programs with respect to data from a clinical trial. The criteria include assessments of changes in both weight-related factors (e.g.

Baseline predictors of success when comparing two treatments.

Since few medications are equally effective in all patients, physicians can maximize the risk/benefit ratio of therapy for their patients by limiting exposure based on baseline predictors of success. Traditional procedures typically evaluate the response of patients receiving the same treatment regimen without evaluating a comparator. However, when treatments are compared, such as in clinical trials, traditional procedures of identifying predictors must be modified to analyze the treatment effect on the primary outcome variable.