Specificity profile of paroxetine in major depressive disorder: Meta-regression of double-blind, randomized clinical trials

Serretti, Alessandro; Gibiino, Sara; Drago, Antonio

doi:10.1016/j.jad.2010.08.018

Cited by 9 publications

(11 citation statements)

References 91 publications

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“…19 A later review of 15 randomized, placebo-controlled trials (RCTs) supported the possibility of better responses to SSRIs in women when compared to men. 20 Consistently, a meta-analysis suggested a possible better response of females to the SSRI paroxetine, 21 while a metaregression analysis of 59 studies found a possible better trend in females after 6 weeks-treatment with sertraline. 22 In line with these findings, preliminary results in a small sample of young men and premenopausal women suggested a greater response in females treated with the SSRI citalopram than in females treated with the SNRI reboxetine, while no differences were observed in men.…”

Section: Sociodemographic Variables Gendermentioning

confidence: 96%

“…25 Finally, some indications of more favorable responses to MAOIs 26 and the SNRI venlafaxine in females were found. 20,21 However, many authors claim that these gender differences in treatment response, although statistically significant, are not large enough to suggest that gender should guide the clinical use of antidepressants. 20,21,26,27 Moreover, other findings failed to reveal any gender effects in predicting or moderating differential responses to different antidepressant classes or compounds.…”

Section: Sociodemographic Variables Gendermentioning

confidence: 99%

“…20,21 However, many authors claim that these gender differences in treatment response, although statistically significant, are not large enough to suggest that gender should guide the clinical use of antidepressants. 20,21,26,27 Moreover, other findings failed to reveal any gender effects in predicting or moderating differential responses to different antidepressant classes or compounds. Indeed, retrospective examinations of multiple RCTs did not find gender differences in responses to TCAs, the SSRI fluoxetine, 26,28 or venlafaxine; 24 similarly, no effects of gender or menopausal status on treatment outcomes with venlafaxine or fluoxetine were found in a large, multiphase, multicenter trial.…”

Section: Sociodemographic Variables Gendermentioning

confidence: 99%

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Personalized Psychiatry and Depression: The Role of Sociodemographic and Clinical Variables

Perna

Alciati²,

Daccò

et al. 2020

Psychiatry Investig

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Despite several pharmacological options, the clinical outcomes of major depressive disorder (MDD) are often unsatisfactory. Personalized psychiatry attempts to tailor therapeutic interventions according to each patient’s unique profile and characteristics. This approach can be a crucial strategy in improving pharmacological outcomes in MDD and overcoming trial-and-error treatment choices. In this narrative review, we evaluate whether sociodemographic (i.e., gender, age, race/ethnicity, and socioeconomic status) and clinical [i.e., body mass index (BMI), severity of depressive symptoms, and symptom profiles] variables that are easily assessable in clinical practice may help clinicians to optimize the selection of antidepressant treatment for each patient with MDD at the early stages of the disorder. We found that several variables were associated with poorer outcomes for all antidepressants. However, only preliminary associations were found between some clinical variables (i.e., BMI, anhedonia, and MDD with melancholic/atypical features) and possible benefits with some specific antidepressants. Finally, in clinical practice, the assessment of sociodemographic and clinical variables considered in our review can be valuable for early identification of depressed individuals at high risk for poor responses to antidepressants, but there are not enough data on which to ground any reliable selection of specific antidepressant class or compounds. Recent advances in computational resources, such as machine learning techniques, which are able to integrate multiple potential predictors, such as individual/ clinical variables, biomarkers, and genetic factors, may offer future reliable tools to guide personalized antidepressant choice for each patient with MDD.

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Section: Sociodemographic Variables Gendermentioning

confidence: 96%

Section: Sociodemographic Variables Gendermentioning

confidence: 99%

Section: Sociodemographic Variables Gendermentioning

confidence: 99%

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Personalized Psychiatry and Depression: The Role of Sociodemographic and Clinical Variables

Perna

Alciati²,

Daccò

et al. 2020

Psychiatry Investig

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“…Most RCTs in mental health now last only 6-8 weeks, which is more economical than a 12-week or longer trial more typical a decade ago (see, for example [21]). But clinicians have to make decisions about long-term treatment for their patients, usually based on this very short-term information.…”

Section: Introductionmentioning

confidence: 99%

“…• A final adverse side effect of the high costs of RCTs, at least with regard to psychiatric drugs, is the brief intervention period that is typically employed to evaluate efficacy. Most RCTs in mental health now last only 6-8 weeks, which is more economical than a 12-week or longer trial more typical a decade ago (see, for example [ 21 ]). But clinicians have to make decisions about long-term treatment for their patients, usually based on this very short-term information.…”

Section: Introductionmentioning

confidence: 99%

Evaluating treatments in health care: The instability of a one-legged stool

Kaplan

Giesbrecht

Shannon

et al. 2011

BMC Med Res Methodol

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BackgroundBoth scientists and the public routinely refer to randomized controlled trials (RCTs) as being the 'gold standard' of scientific evidence. Although there is no question that placebo-controlled RCTs play a significant role in the evaluation of new pharmaceutical treatments, especially when it is important to rule out placebo effects, they have many inherent limitations which constrain their ability to inform medical decision making. The purpose of this paper is to raise questions about over-reliance on RCTs and to point out an additional perspective for evaluating healthcare evidence, as embodied in the Hill criteria. The arguments presented here are generally relevant to all areas of health care, though mental health applications provide the primary context for this essay.DiscussionThis article first traces the history of RCTs, and then evaluates five of their major limitations: they often lack external validity, they have the potential for increasing health risk in the general population, they are no less likely to overestimate treatment effects than many other methods, they make a relatively weak contribution to clinical practice, and they are excessively expensive (leading to several additional vulnerabilities in the quality of evidence produced). Next, the nine Hill criteria are presented and discussed as a richer approach to the evaluation of health care treatments. Reliance on these multi-faceted criteria requires more analytical thinking than simply examining RCT data, but will also enhance confidence in the evaluation of novel treatments.SummaryExcessive reliance on RCTs tends to stifle funding of other types of research, and publication of other forms of evidence. We call upon our research and clinical colleagues to consider additional methods of evaluating data, such as the Hill criteria. Over-reliance on RCTs is similar to resting all of health care evidence on a one-legged stool.

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Sex Differences in Human Lymphoblastoid Cells Sensitivities to Antipsychotic Drugs

2012

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Specificity profile of paroxetine in major depressive disorder: Meta-regression of double-blind, randomized clinical trials

Cited by 9 publications

References 91 publications

Personalized Psychiatry and Depression: The Role of Sociodemographic and Clinical Variables

Personalized Psychiatry and Depression: The Role of Sociodemographic and Clinical Variables

Evaluating treatments in health care: The instability of a one-legged stool

Sex Differences in Human Lymphoblastoid Cells Sensitivities to Antipsychotic Drugs

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