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. We validate our findings with known examples from the literature and experimentation. From this model, we rank each potential operon pair by the strength of evidence for cotranscription, choose a classification threshold with a true positive rate of over 90% at a false positive rate of 9.1%, and use it to construct an operon map for the MTB genome.

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. METHODS: Patients with major depression who met the study's response criteria (a modified Hamilton Depression Rating Scale score < or =7 and failure to meet major depression criteria after each of the last 3 weeks following 12 to 14 weeks of treatment with fluoxetine hydrochloride, 20 mg/d) were enrolled in a 50-week randomized placebo substitution trial during which the return of depressive symptoms defined relapse. The timing and persistency of response during initial treatment defined true drug or placebo response patterns. RESULTS: Patients with a true drug response pattern relapsed significantly more frequently if they were switched to placebo than if they continued to receive fluoxetine (P<.001 for weeks 12-26, P<.005 for weeks 26-50, and P<.41 for weeks 50-62). Patients with a placebo response pattern had an equivalent outcome whether maintained on fluoxetine therapy or placebo (P< .20 for weeks 12-26, test invalid for weeks 26-50, and P<.67 for weeks 50-62). Patients with a placebo response pattern relapsed more often when they continued to receive fluoxetine than patients with a true drug response pattern (P<.01 for weeks 12-26, P<.10 for weeks 26-50, and P<.36 for weeks 50-62). CONCLUSIONS: These findings confirm that pattern analysis validly differentiates true drug from nonspecific initial responses and extend its use to the continuation and maintenance phases of treatment for depression. Investigations into the mechanisms of antidepressant activity might best be limited to those that can account for delayed efficacy. Fluoxetine's efficacy during the continuation and maintenance phases of treatment may be limited to patients with a true drug pattern of initial response.

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). Relapse rate was the primary outcome measure. Both Kaplan-Meier estimates and observed relapse rates were assessed in three fixed 12-week intervals after double-blind transfers from fluoxetine to placebo at the start of the double-blind period and after 14 and 38 weeks of continued fluoxetine treatment. RESULTS: Relapse rates (Kaplan-Meier estimates) were lower among the patients who continued to take fluoxetine compared with those transferred to placebo in both the first interval, after 24 total weeks of treatment (fluoxetine, 26.4%; placebo, 48.6%), and the second interval, after 38 total weeks of treatment (fluoxetine, 9.0%; placebo, 23.2%). In the third interval, after 62 total weeks of treatment, rates were not significantly different between the groups (fluoxetine, 10.7%; placebo, 16.2%). CONCLUSIONS: Patients treated with fluoxetine for 12 weeks whose depressive symptoms remit should continue treatment with fluoxetine for at least an additional 26 weeks to minimize the risk of relapse.

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. excess weight, excess body fat) and obesity-related risk factors (e.g. hypertension, hyperglycemia, hyperlipemia). To demonstrate the use of this methodology, we applied the criteria in an analysis of eight randomized, double-blind controlled trials comparing fluoxetine (n = 522) with placebo (n = 504) for weight loss. The results suggest these criteria can be useful for evaluating a treatment program or for comparing treatments from clinical trials.

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. We focus on clinical and statistical considerations that arise when developing baseline predictors through models which consider treatment differences. To illustrate an application of this method, we used data from 1,026 patients completing at least 6 months of double-blind therapy in clinical trials comparing fluoxetine (N=522) with placebo (N=504) for weight loss. Stepwise regression procedures were used to identify baseline variables which were predictive of a beneficial fluoxetine treatment effect on last-visit-carried-forward (LVCF) weight change. In this example, age, smoking activity, and uric acid concentration were the best baseline predictors of long-term treatment effect relative to LVCF weight change. Patients were more likely to achieve long-term benefit with fluoxetine if they were older, and/or were nonsmokers, and/or had high concentrations of uric acid at baseline. These predictors, developed through models keying on treatment effect, can be used to identify patients who are more likely to accrue benefits with active therapy beyond those expected with placebo therapy, thus enriching the treatment population so that a higher proportion of treated patients are successful.

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. Analyses of SF-36 changed scores from baseline to Week 6 revealed that the fluoxetine group improved more than the placebo group across all scales. Differences in changes of scores between groups were significant (p < .05), favoring the fluoxetine group for the scales of mental health, role limitations due to emotional problems, physical functioning, and bodily pain. Improvements observed in the fluoxetine group were both clinically and socially significant.

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. Extended therapy with fluoxetine has demonstrated clinically meaningful benefits on weight loss and obesity-associated medical conditions in double-blind placebo-controlled studies. However, the magnitude of these benefits for individuals vary. Such findings are consistent with the belief that the obesity syndrome has differing etiologies. Accordingly not all patients are likely to benefit from a particular therapy. Studies should identify patient subgroups that are more likely to respond to a specific therapy. In this study of 719 fluoxetine-treated and 722 placebo treated patients in four multicenter, randomized, double-blind, long-term clinical trials, we investigated possible predictors of a beneficial long-term outcome from fluoxetine therapy. Patients' age, current smoking activity, and baseline uric acid concentration were predictors of a meaningful long-term treatment effect. Further review of the weight loss patterns of patients achieving long-term success provided the basis for a treatment monitor. Use of the predictors and the treatment monitor are strategies to maximize the benefits of therapy through improved patient selection and monitoring during a therapeutic program.