Meta-analyses of antidepressant
efficacy based on data from published trials reveal benefits that are statistically significant, but of marginal clinical
significance [1]. Analyses of datasets including unpublished as well as published clinical trials reveal smaller effects that fall well below
recommended criteria for clinical effectiveness. Specifically, a meta-analysis of clinical trial data submitted to the US
Food and Drug Administration (FDA) revealed a mean drug–placebo difference in improvement scores of 1.80 points on the
Hamilton Rating Scale of Depression (HRSD) [2], whereas the National Institute for Clinical Excellence (NICE) used a drug–placebo difference
of three points as a criterion for clinical significance when establishing guidelines for the treatment of depression in the
United Kingdom [1]. Mean improvement scores can obscure differences in improvement within subsets of patients. Specifically, antidepressants
may be effective for severely depressed patients, but not for moderately depressed patients [1,3,4]. The purpose of the present analysis is to test that hypothesis (see Text S1 for the QUOROM checklist).
Conventional meta-analyses are
often limited to published data. In the case of antidepressant medication, this limitation has been found to result in considerable
reporting bias characterized by multiple publication, selective publication, and selective reporting in studies sponsored
by pharmaceutical companies [5]. To avoid publication bias, we evaluated a dataset that includes the complete data from all trials of the medications, whether
or not they were published. Specifically, we analyzed the data submitted to the FDA for the licensing of four new-generation
antidepressants for which full data, published and unpublished, were available. As part of the licensing process, the FDA
requires drug companies to report “all controlled studies related to each proposed indication” ([6] emphasis in original). Thus, there should be no reporting bias in the dataset we analyze.
Methods
Study Retrieval
Following the Freedom of Information Act (FOIA) [7], we requested from the FDA all publicly releasable information about the clinical trials for efficacy conducted for marketing
approval of fluoxetine, venlafaxine, nefazodone, paroxetine, sertraline, and citalopram, the six most widely prescribed antidepressants
approved between 1987 and 1999 [2], which represent all but one of the selective serotonin reuptake inhibitors (SSRIs) approved during the study period. In
reply, the agency provided photocopies of the medical and statistical reviews of the sponsors' New Drug Applications. The
FDA requires that information on all industry-sponsored trials be submitted as part of the approval process; hence the files
sent to us by the FDA should contain information on all trials conducted prior to the approval of each medication. This strategy
omits trials conducted after approval was granted.
Although sponsors are required to submit information on all trials, the FDA public disclosure did not include mean changes
for nine trials that were deemed adequate and well controlled but that failed to achieve a statistically significant benefit
for drug over placebo. Data for four of these trials were available from a pharmaceutical company Web site in January 2007
and were obtained from the GlaxoSmithKline clinical trial register (http://ctr.gsk.co.uk/Summary/paroxetine/studylist.asp).
We also identified published versions of the FDA trials via a PubMed literature search (from January 1985 through May
2007) using the keywords depression; depressive;
depressed; and placebo;
specific names of antidepressant medications; and names of investigators from the FDA trials. Potentially relevant studies
were also identified through references of retrieved and review articles and from a partially overlapping list of published
versions of trials submitted to the Swedish drug regulatory authority [5]. Using a standardized protocol, all retrieved abstracts and publications were compared to the FDA trials. The match between
each published study and its corresponding FDA trial was independently established with 100% agreement by two investigators
(BJD and a research assistant).
Selection
Forty-seven clinical trials were identified in the data obtained from the FDA. The trial flow is illustrated in Figure 1. Inclusion of a drug type for which unsuccessful trials were excluded biases overall results in favor of that drug type,
in a way that is akin to publication bias. The purpose in using the FDA dataset is precisely to avoid this type of bias by
including all trials of each medication assessed. Therefore, we present analyses only for those medications for which mean
change scores on all trials were available.
Assessment
The FDA requires that rigorous
standards be followed for the conduct of all efficacy trials for marketing approval [8] and also sets specific agency standards for clinical trials of antidepressant drugs [9]. In addition, the FDA independently reviews the clinical trial methods, statistical procedures, and results. The FDA dataset
includes analyses of data from all patients who attended at least one evaluation visit, even if they subsequently dropped
out of the trial prematurely. Results are reported from all well-controlled efficacy trials of the use of these medications
for the treatment of depression. FDA medical and statistical reviewers had access to the raw data and evaluated the trials
independently. The findings of the primary medical and statistical reviewers were verified by at least one other reviewer,
and the analysis was also assessed by an independent advisory panel. Following FDA standards, all trials were randomized,
double-blind, placebo-controlled trials. None used cross-over designs. Patients had been diagnosed as suffering from unipolar
major depressive disorder using Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria.
Given the above review process,
we deemed it appropriate to include all studies deemed adequate and well controlled by FDA reviewers, especially as these
are the data upon which the decision to approve these medications was based. Other validity criteria might yield different
conclusions. In this review, some of the characteristics that may relate to the quality of trials were coded and assessed
as possible moderator variables (e.g., interval of trial). The studies have similar methodological characteristics and were
well controlled; therefore the methodological characteristics did not affect the final results.
Study Characteristics
In order to generalize the findings
of the clinical trial to a larger patient population, FDA reviewers sought a completion rate of 70% or better for these typically
6-wk trials. Only four of the trials reported reaching this objective, and completion rates were not reported for two trials.
Attrition rates were comparable between drug and placebo groups. Of those trials for which these rates were reported, 60%
of the placebo patients and 63% of the study drug patients completed a 4-, 5-, 6-, or 8-wk trial. Thirty-three trials were
of 6-wk duration, six trials were 4 wk, two were 5 wk, and six were 8 wk. Patients were evaluated on a weekly basis. For this
meta-analysis, the data were taken from the last visit prior to trial termination.
Thirty-nine trials focused on
outpatients: three included both inpatients and outpatients, three were conducted among the elderly (including one of the
trials with both inpatients and outpatients), and two were among patients hospitalized for severe depression. No trial was
reported for the treatment of children or adolescents.
Replacement of patients who investigators
determined were not improving after 2 wk was allowed in three fluoxetine trials and in the three sertraline trials for which
data were reported. The trials also included a 1- to 2-wk washout period during which patients were given placebo, prior to
random assignment. Those whose scores improved 20% or more were excluded from the study prior to random assignment. The use
of other psychoactive medication was reported in 25 trials. In most trials, a chloral hydrate sedative was permitted in doses
ranging from 500 mg to 2,000 mg per day. Other psychoactive medication was usually prohibited but still reported as having
been taken in several trials.
Meta-Analytic Data Synthesis
We conducted two types of data
analysis, one in which each group's change was represented as a standardized mean difference (d), which divides change by the standard deviation of the
change score (SDc) [10], and another using each study's drug and placebo groups' arithmetic mean (weighted for the inverse of the variance) as the
meta-analytic “effect size” [11].
The first analysis permitted a
determination of the absolute magnitude of change in both the placebo and treatment groups. Results permitted a determination
of overall trends, analyses of baseline scores in relation to change, and for both types of models, tests of model specification,
which assess the extent to which only sampling error remains unexplained. The results in raw metric are presented comparing
both groups, but because of the variation of the SDcs, the standardized mean difference was used in moderator analyses in order to attain better-fitting
models [12]. These results are compared to the criterion for clinical significance used by NICE, which is a three-point difference in Hamilton Rating Scale
of Depression (HRSD) scores or a standardized mean difference (d) of 0.50 [1].
As known SDcs were related to mean baseline HRSD scores, these scores
were used to impute missing SDc values, taking into account both the baseline and its quadratic form and any potential interaction of these terms with
group (but in fact, there was no evidence that SDcs depended on treatment group). One trial reported SDcs for its drug and placebo groups that were less than 25%
the size of the other trials; because preliminary analyses also revealed that this trial was an outlier, these two standard
deviations were treated as missing and imputed. In total, SDcs were known for 28 groups, could be calculated from other inferential statistics in nine
comparisons (18 groups), and were imputed in 12 comparisons (24 groups) (47.38%) [13,14].
Overall analyses evaluated both
random- and fixed-effects models to assess effect size magnitude; because the same trends appeared for both, for simplicity
we present only the fixed-effects results. We also assumed fixed-effects assumptions in order to analyze moderators for both
groups. Both Q [15] and I2 [16] indices were used to assess inconsistencies from the models, not only to infer the presence or absence of homogeneity, but
also (in the case of I2) to assess the degree of inconsistencies among trials [17]. We assumed fixed-effects models in analyzing moderators using meta-regression procedures [11]. Analyses examining linear and quadratic functions for baseline levels of severity used zero-centered forms of this variable
[18]. A last, mixed-effects analysis for the amount of change used a random-effects constant along with fixed-effects moderator
dimensions; these models provide more conservative assessments of moderation [19].
Because the same scale was used
as the primary dependent variable in all of these trials, we were also able to represent results in their original metric
[11]. This form of analysis makes results more easily interpretable in terms of clinical significance because mean change scores
are analyzed directly, rather than being converted into effect sizes. The analytic weights are derived from the sample size
and the SDc [11]. Finally, to show directly the amount of improvement for each study's drug group against its placebo group, we calculated
the difference between the change for the drug group minus the change for the placebo group, leaving the difference in raw
units and deriving its analytic weight from its standard error [11,12,20]. Analyses used these weights to examine these controlled outcomes both overall and to determine the extent to which drug-related
change is a function of initial severity.
Results
Trial Flow
Mean improvement scores were not available in five of the 47 trials (Figure 1). Specifically, four sertraline trials involving 486 participants and one citalopram trial involving 274 participants were
reported as having failed to achieve a statistically significant drug effect, without reporting mean HRSD scores. We were
unable to find data from these trials on pharmaceutical company Web sites or through our search of the published literature.
These omissions represent 38% of patients in sertraline trials and 23% of patients in citalopram trials. Analyses with and
without inclusion of these trials found no differences in the patterns of results; similarly, the revealed patterns do not
interact with drug type. The purpose of using the data obtained from the FDA was to avoid publication bias, by including unpublished
as well as published trials. Inclusion of only those sertraline and citalopram trials for which means were reported to the
FDA would constitute a form of reporting bias similar to publication bias and would lead to overestimation of drug–placebo
differences for these drug types. Therefore, we present analyses only on data for medications for which complete clinical
trials' change was reported. The dataset comprised 35 clinical trials (five of fluoxetine, six of venlafaxine, eight of nefazodone,
and 16 of paroxetine) involving 5,133 patients, 3,292 of whom had been randomized to medication and 1,841 of whom had been
randomized to placebo.
Mean Change
Baseline HRSD scores, improvement, and sample sizes in drug and placebo groups for each clinical trial are reported in
Table 1. As in the FDA files, studies are identified by protocol numbers. The data from these trials can be obtained from the FDA
using FOIA requests and citing the medication name and protocol number. The table also includes references to published reports
of the data abstracted from the FDA files, when they could be found (using the search methods described above). Studies in
which data only from selected sites of a multisite study were published are not cited in the table. We have also excluded
published reports in which dropouts have been removed from the data. For each of the trials, the pharmaceutical companies
had submitted to the FDA data in which attrition was handled by carrying forward the last observation carried forward (LOCF)
on the patient, which was the basis in all cases of the FDA review. These data and their corresponding citations appear in
the table. Even in the LOCF data, there sometimes are some minor discrepancies between the published version and the version
submitted to the FDA. In some cases, for example, the N is slightly larger
in the published studies than in the data reported to the FDA. Further complicating this problem is the fact that occasionally,
the company has published a trial more than once, with slight discrepancies in the data between publications. Data in the
table are those reported to the FDA.
Drug and Initial Severity Trends in Change
Moderator analyses examined whether drug type, duration of treatment, and baseline severity (HRSD) scores related to improvement.
Although drug type and duration of treatment were unrelated to improvement, the drug versus placebo difference remained significant,
and amount of improvement was a function of baseline severity (Table 2, Model 1a). Specifically, the amount of improvement depended markedly on the quadratic function of baseline severity, but
the linear function of baseline severity interacted with assignment to drug versus placebo (Model 1b). Specifically, as Figure 2 shows, improvement from baseline operated as a -shaped curvilinear
function in relation to baseline severity, with those at the lowest and highest levels experiencing smaller gains, whereas
those in-between experienced larger gains; the slope for placebo declined as severity increased, whereas the slope for drug
was slightly positive. The difference between drug and placebo exceeded NICE's 0.50 standardized mean difference criterion at comparisons
exceeding 28 in baseline severity. Further analyses indicated that drug type did not moderate this affect. Although venlafaxine
and paroxetine had significantly (p < 0.001) larger weighted mean effect
sizes comparing drug to placebo conditions (ds = 0.42 and 0.47, respectively)
than fluoxetine (d = 0.22) or nefazodone (0.21), these differences disappeared
when baseline severity was controlled.
For all but one sample, baseline HRSD scores were in the very severe range according to the criteria proposed by the American
Psychiatric Association (APA) [21] and adopted by NICE [1]. The one exception derived from a fluoxetine trial that had two samples, one with HRSD scores in the very severe range and
the other with scores in the moderate range. Because the low-HRSD condition might be considered an outlier, the analyses were
performed again without it. Results continued to reveal that drug versus placebo assignment interacted with initial severity
to influence improvement; yet the curvilinear function of the baseline was no longer significant, although group continued
to interact with the linear component (Table 2, Model 2c). As Figure 3 shows, drug efficacy did not change as a function of initial severity, whereas placebo efficacy decreased as initial severity
increased; values again exceeded NICE's 0.50 standardized mean difference criterion at comparisons greater than 28 in baseline
severity. This final model comprising three simultaneous study dimensions (viz., drug vs. placebo, baseline, and the interaction)
explained 51.45% of the variation in improvement. Although this model was in a formal sense incorrectly specified (QResidual(64) = 96.07, p
< 0.01), when a random-effects constant was instead assumed, the same pattern of results remained in this more statistically
conservative mixed-effects model. A final model that incorporated even the drug types for which only some trials were available
confirmed these trends.
{Clinical signficant nixed graph} For a difference from placebo to singificant
improvement has to have a rating of 3}
Figure 4 displays raw mean differences between drug and placebo as a function of initial severity, rising as a linear function of
baseline severity levels (Table 2, Models 3a and 3b) even though, almost without exception, the scores were in the very severe range of the criteria proposed
by APA [21]. Yet when these data are considered in conjunction with those in Figure 3, it seems clear that the increased difference is due to a decrease in improvement in placebo groups, rather than an increase
in drug groups.
visual inspection of Figure 4 suggests that studies' effects are fairly evenly distributed above and below the NICE criterion (3) but that most small studies have high baselines
and show large effects. Although sample size (N) was negatively linked to the drug-versus-placebo differences (β = −0.34,
p = 0.003),
when mean baseline severity values are controlled, this effect disappears and the baseline effect remains significant. The
interaction of sample size with baseline severity was marginally significant, p = 0.0586, and the pattern indicated that baseline severity
was somewhat more predictive for smaller than for larger studies. Yet, because simple-slopes analyses revealed that baseline
scores were significantly predictive even for the largest studies, study differences in sample size would appear to qualify
neither the pattern of results we have reported nor their interpretation.
Examination of publication bias
often relies on inspections of effect sizes in relation to sample size (or inverse variance) [22]. A funnel plot of the data depicted in Figure 4 indicates that the larger studies in the FDA datasets tended to show smaller drug effects than smaller studies. Although
such a pattern might be construed as indicating a publication or other reporting bias, our use of complete datasets precludes
this possibility, unless some small trials were not reported despite the FDA Guidelines [6]. A more plausible explanation is that trials with higher baseline scores tended to be small. In any case, funnel-plot inspections
assume that there is only one population effect size that can be tracked by a comparison between drug and placebo groups,
whereas the current investigation shows that these effects vary widely and that the magnitude of the difference depends on
initial severity values. Consequently, funnel-plot inspection is much less appropriate in the present context. Unfortunately,
there are no other tools yet available to detect publication or other reporting biases in the face of effect modifiers.
Discussion
Using complete datasets (including
unpublished data) and a substantially larger dataset of this type than has been previously reported, we find that the overall
effect of new-generation antidepressant medications is below recommended criteria for clinical significance. We also find
that efficacy reaches clinical significance only in trials involving the most extremely depressed patients, and that this
pattern is due to a decrease in the response to placebo rather than an increase in the response to medication.
Similar to prior reports [3,4], this analysis of U.S. FDA data for four new-generation antidepressants suggests an association between initial severity
and the benefit of antidepressant medication. Unlike prior studies, we restricted our analysis to complete datasets that included
all trials conducted, whether published or not. Thus, simple publication bias cannot underlie the results. We compared drug–placebo
differences in improvement to criteria for clinical efficacy, and we used meta-regression procedures [11] to identify the relation of severity to improvement. Although we were able to replicate previously reported decreases in
the placebo response as a function of increasing baseline severity, we found no linear relation between severity and response
to medication.
NICE used a three-point difference
in HRSD change scores, or a standardized mean difference of 0.50, as criteria of clinical significance [1]. By that criterion, the differences between drug and placebo were not clinically significant in clinical trials involving
either moderately or very severely depressed patients, but did reach the criterion for trials involving patients whose mean
initial depression scores were at the upper end of the very severe depression category (mean HRSD baseline 28; Figures 2–4). Given these data, there seems little evidence to support the prescription of antidepressant medication to any but the most
severely depressed patients, unless alternative treatments have failed to provide benefit.
A prior meta-analysis of published
data only reported a very small significant difference between the antidepressant effect of fluoxetine and venlafaxine, but
did not assess the effect of baseline severity as a moderator [23]. Our analyses failed to reveal any effect of drug type on efficacy or on the relation between severity and efficacy. It
is possible that differences associated with drug type might be found with the inclusion of clinical trials conducted after
the approval process, but analyses of head-to-head comparisons suggest that they are not likely to be large enough to be of
clinical importance [23].
The response to placebo in these
trials was exceptionally large, duplicating more than 80% of the improvement observed in the drug groups. In contrast, the
effect of placebo on pain is estimated to be about 50% of the response to pain medication [24–26]. A substantial response to placebo was seen in moderately depressed groups and in groups with very severe levels of depression.
It decreased somewhat, but was still substantial, in groups with the most-severe levels of depression.
Although baseline severity related
to degree of improvement in the drug groups, the pattern was not linear. Instead, patients who by APA criteria were moderately depressed
and those at the very high end of the severely depressed category (i.e., those with initial HRSD scores greater than 28) showed
less improvement than those at the lower end of the severely depressed category. The curvilinear relation depended on only
one trial of moderately depressed patients. When that outlier trial is excluded, there is no relation between baseline severity
and antidepressant response. However, all of the other trials were with groups with mean initial HRSD scores in the very severe
range (i.e., 23). What
is missing from the FDA data, however, are clinical trials with patients with initial depression scores in the severe range
(19–22), and there was only one study with patients in the moderately depressed range. Had groups with a wider array
of baseline depression scores been assessed, the curvilinear pattern might have been more obvious; in which case, clinically
significant benefits for severely depressed patients might have been obtained. To perform this task in an unbiased way, it
would be necessary for data for all approved medications to be available, even those gathered after the medication is approved.
Having all the information available would also obviate the need to impute missing standard deviations, a limitation of the
current investigation. Public availability of complete data on approved mediations might be made a condition of approval to
solve these problems.
Finally, although differences
in improvement increased at higher levels of initial depression, there was a negative relation between severity and the placebo
response, whereas there was no difference between those with relatively low and relatively high initial depression in their
response to drug. Thus, the increased benefit for extremely depressed patients seems attributable to a decrease in responsiveness
to placebo, rather than an increase in responsiveness to medication.
Supporting
Information
Text S1. QUOROM Checklist
(33 KB DOC)
Acknowledgments
Author contributions. IK abstracted baseline data from the FDA dataset, conceived the analyses, analyzed the data, and wrote the initial draft.
BJD established correspondence between trials reported in the FDA dataset and those reported in the GlaxoSmithKline clinical
trial register, abstracted the data from those trials, checked baseline data for trials in the FDA dataset, identified published
versions of the FDA trials, and abstracted the data from those trials. TJM obtained the data from the FDA, and TJM and AS
abstracted improvement data from that dataset. TBH and BTJ joined the project during the review process, analyzed the data, and
assisted with subsequent drafts of the manuscript.
References
1.
National
Institute for Clinical Excellence (2004) Depression: management of depression in primary and secondary care. Clinical practice
guideline No 23 London: National Institute for Clinical Excellence. 670 p.
2.
Kirsch
I, Moore TJ, Scoboria A, Nicholls SS (2002) The emperor's new drugs: an analysis of antidepressant medication data submitted
to the U.S. Food and Drug Administration. Prev Treat 5. article 23. Available: http://www.journals.apa.org/prevention/volume5/pre0050023a.html. Accessed 15 July 2002.
3.
Angst
J (1993) Severity of depression and benzodiazepine co-medication in relationship to efficacy of antidepressants in acute trials:
a meta-analysis of moclobemide trials. Hum Psychopharmacol 8: 401–407. Find this article online
4.
Khan
A, Leventhal R, Khan S, et al. (2002) Severity of depression and response to antidepressants and placebo: an analysis of the
Food and Drug Administration database. J Clin Psychopharmacol 22: 40–45. Find this article online
5.
Melander
H, Ahlqvist-Rastad J, Meijer G, Beermann B (2003) Evidence b(i)ased medicine—selective reporting from studies sponsored
by pharmaceutical industry: review of studies in new drug applications. BMJ 326: 1171–1173. Find this article online
6.
Center
for Drug Evaluation and Research (1987) Guidance for industry: guideline for the format and content of the summary for new
drug and antibiotic applications Rockville (Maryland): U.S. Department of Health, Education, and Welfare. Food and Drug Administration.
Available: http://www.fda.gov/cder/guidance/old038fn.pdf. Accessed 27 October 2007.
7.
Freedom
of Information Act (FOIA). 5 US Congress. 552 (1994 & Supp. II 1996).
8.
Center
for Drug Evaluation and Research (1996) Guidance for industry: good clinical practice: consolidated guidance Rockville (Maryland):
U.S. Department of Health, Education, and Welfare. Food and Drug Administration. Available: http://www.fda.gov/cder/guidance/959fnl.pdf. Accessed 27 October 2007.
9.
Center
for Drug Evaluation and Research (1977) Guidance for industry: guidelines for the clinical evaluation of antidepressant drugs
Rockville (Maryland): U.S. Department of Health, Education, and Welfare. Food and Drug Administration. Available: http://www.fda.gov/cder/guidance/old050fn.pdf. Accessed 27 October 2007.
10.
Gibbons
RD, Hedeker DR, Davis JM (1993) Estimation of effect size from a series of experiments involving paired comparisons. J Educ
Stat 18: 271–279. Find this article online
11.
Lipsey
MW, Wilson DB (2001) Practical meta-analysis. Applied social research methods Volume 49. Thousand Oaks (California): Sage
Publications. 247 p.
12.
Bond
CF, Wiitala WL, Richard FD (2003) Meta-analysis of raw mean differences. Psychol Methods 8: 206–418. Find this article online
13.
Furukawa
TA, Barbui C, Cipriani A (2006) Imputing missing standard deviations in meta-analyses can provide accurate results. J Clin
Epidemiol 59: 7–10. Find this article online
14.
Thiessen-Philbrook
H, Barrowman N, Garg AX (2007) Imputing variance estimates do not alter the conclusions of a meta-analysis with continuous
outcomes: a case study of changes in renal function after living kidney donation. J Clin Epidemiol 60: 228–240. Find this article online
15.
Hedges
LV, Olkin I (1985) Statistical methods for meta-analysis New York: Academic Press. 369 p.
16.
Higgins
JPT, Thompson SG (2002) Measuring inconsistency in meta-analyses. Educ Debate 327: 557–560. Find this article online
17.
Huedo-Medina
TB, Johnson BT (2007) I2 is subject to the same statistical power problems as Cochran's Q [Letter]. BMJ Available: http://www.bmj.com/cgi/eletters/327/7414/557. Accessed 23 January 2008.
18.
Thompson
SG, Smith TC, Sharp SJ (1997) Investigating underlying risk as a source of heterogeneity in meta-analysis. Stat Med 16: 2741–2758.
Find this article online
19.
Hedges
LV, Pigott TD (2004) The power of statistical tests for moderators in meta-analysis. Psychol Methods 9: 426–445. Find this article online
20.
Glass
GV, McGaw B, Smith ML (1981) Meta-analysis in social research Beverly Hills (California): Sage Publications. 279 p.
21.
American
Psychiatric Association. Task Force for the Handbook of Psychiatric Measures (2000) Handbook of psychiatric measures Washington
(D. C.): American Psychiatric Association. 820 p.
22.
Thornton
A, Lee P (2000) Publication bias in meta-analysis: its causes and consequences. J Clin Epidemiol 53: 207–216. Find this article online
23.
Hansen
RA, Gartlehner G, Lohr KN, Gaynes BN, Carey TS (2005) Efficacy and safety of second-generation antidepressants in the treatment
of major depressive disorder. Ann Intern Med 143: 415–426. Find this article online
24.
Evans
FJ (1974) The placebo response in pain reduction. Adv Neurol 4: 289–296. Find this article online
25.
Benedetti
F, Arduino C, Amanzio M (1999) Somatotopic activation of opioid systems by target-directed expectations of analgesia. J Neurosci
19: 3639–3648. Find this article online
26.
Evans
FG (1985) Expectancy, therapeutic instructions, and the placebo response. In: White L, Tursky B, Schwartz GE Placebo: theory,
research and mechanisms New York: Guilford Press. pp. 215–228.
27.
Fabre
LF, Crimson L (1985) Efficacy of fluoxetine in outpatients with major depression. Curr Ther Res Clin Exp 37: 115–123.
Find this article online
28.
Stark
P, Hardison CD (1985) A review of multicenter controlled studies of fluoxetine vs. imipramine and placebo in outpatients with
major depressive disorder. J Clin Psychiatry 46: 53–58. Find this article online
29.
Dunlop
SR, Dornseif BE, Wernike JF, Potvin JH (1990) Pattern analysis shows beneficial effect of fluoxetine treatment in major depression.
Psychopharmacol Bull 26: 173–180. Find this article online
30.
Rudolph
RL, Fabre LF, Feighner JP, Rickels K, Entsuah R, et al. (1998) A randomized, placebo-controlled, dose-response trial of venlafaxine
hydrochloride in the treatment of major depression. J Clin Psychiatry 5: 116–122. Find this article online
31.
Ballenger
J (1996) Clinical evaluation of venlafaxine. J Clin Psychopharmacol 16(Suppl 2): 29S–36S. Find this article online
32.
Schweizer
E, Feighner J, Mandos LA, Rickels K (1994) Comparison of venlafaxine and imipramine in the acute treatment of major depression
in outpatients. J Clin Psychiatry 55: 104–108. Find this article online
33.
Cunningham
LA, Borison RL, Carman JS, Chouinard G, Crowder JE, et al. (1994) A comparison of venlafaxine, trazodone, and placebo in major
depression. J Clin Psychopharmacol 14: 99–106. Find this article online
34.
Kelsey
JE (1996) Dose-response relationship with venlafaxine. J Clin Psychopharmacol 16(Suppl 2): 21S–26S. Find this article online
35.
Mendels
J, Johnston R, Mattes J, Riesenberg R (1993) Efficacy and safety of b.i.d. doses of venlafaxine in a dose-response study.
Psychopharmacol Bull 29: 169–174. Find this article online
36.
Guelfi
JD, White C, Hackett D, Guichoux JY, Magni G (1995) Effectiveness of venlafaxine in patients hospitalized for major depression
and melancholia. J Clin Psychiatry 56: 450–458. Find this article online
37.
Fintaine
R, Ontiveros A, Elie R, Kensler TT, Roberts DL, et al. (1994) A double-blind comparison of nefazodone, imipramine, and placebo
in major depression. J Clin Psychiatry 55: 234–241. Find this article online
38.
Mendels
J, Reimherr F, Marcus RN, Roberts DL, Francis RJ, et al. (1995) A double-blind, placebo-controlled trial of two dose ranges
of nefazodone in the treatment of depressed outpatients. J Clin Psychiatry 56(Suppl 6): 30–36. Find this article online
39.
D'Amico
MF, Roberts DL, Robinson DS, Schwiderski UE, Copp J (1990) Placebo-controlled dose-ranging trial designs in phase II development
of nefazodone. Psychopharmacol Bull 26: 147–150. Find this article online
40.
Rickels
K, Schweizer E, Clary C, Fox I, Weise C (1994) Nefazodone and imipramine in major depression: a placebo-controlled trial.
Brit J Psychiatry 164: 802–805. Find this article online
41.
Rickels
K, Amsterdam J, Clary C, Fox I, Schweizer E, et al. (1989) A placebo-controlled, double-blind, clinical trial of paroxetine
in depressed outpatients. Acta Psychiatr Scand 80(Suppl 350): 117–123. Find this article online
42.
Rickels
K, Amsterdam J, Clary C, Fox I, Schweizer E, et al. (1992) The efficacy and safety of paroxetine compared with placebo in
outpatients with major depression. J Clin Psychiatry 53(Suppl): 30–32. Find this article online
43.
Claghorn
J (1992) A double-blind comparison of paroxetine and placebo in the treatment of depressed outpatients. Int Clin Psychopharmacol
6(Suppl 4): 25–30. Find this article online
44.
Claghorn
J (1992) The safety and efficacy of paroxetine compared with placebo in a double-blind trial of depressed outpatients. J Clin
Psychiatry 53(Suppl): 33–35. Find this article online
45.
Smith
WT, Glaudin V (1992) A placebo-controlled trial of paroxetine in the treatment of major depression. J Clin Psychiatry 53(Suppl):
36–39. Find this article online
46.
Kiev
A (1992) A double-blind, placebo-controlled study of paroxetine in depressed outpatients. J Clin Psychiatry 53(Suppl): 27–29.
Find this article online
47.
Feighner
JP, Boyer WF (1989) Paroxetine in the treatment of depression: a comparison with imipramine and placebo. Acta Psychiatr Scand
80(Suppl 350): 125–129. Find this article online
48.
Feighner
JP, Boyer WF (1992) Paroxetine in the treatment of depression: a comparison with imipramine and placebo. J Clin Psychiatry
53(Suppl): 44–47. Find this article online
49.
Cohn
JB, Crowder JE, Wilcox CS, Ryan PJ (1990) A placebo- and imipramine-controlled study of paroxetine. Psychopharmacol Bull 26:
185–189. Find this article online
50.
Cohn
JB, Wilcox CS (1992) Paroxetine in major depression: a double-blind trial with imipramine and placebo. J Clin Psychiatry 53(Suppl):
52–56. Find this article online
51.
Shrivastava
RK, Shrivastava SHP, Overweg N, Blumhardt CL (1992) A double-blind comparison of paroxetine, imipramine, and placebo in major
depression. J Clin Psychiatry 53(Suppl): 48–51. Find this article online
52.
Peselow
ED, Filippi AM, Goodnick P, Barouche FB, Fieve RR (1989) The short- and long-term efficacy of paroxetine HCl: A. Data from
a 6-week double-blind parallel design trial vs. imipramine and placebo. Psychopharmacol Bull 25: 267–271. Find this article online
53.
Fabre
LF (1992) A 6-week, double-blind trial of paroxetine, imipramine, and placebo in depressed outpatients. J Clin Psychiatry
53(Suppl): 40–43. Find this article online
54.
Dunner
DL, Dunbar GC (1992) Optimal dose regimen for paroxetine. J Clin Psychiatry 53(Suppl): 21–26. Find this article online
55.
Miller
SM, Naylor GJ, Murtagh M, Winslow G (1989) A double-blind comparison of paroxetine and placebo in the treatment of depressed
patients in a psychiatric outpatient clinic. Acta Psychiatr Scand 80(Suppl 350): 143–144. Find this article online
