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<\/p>\n
Fluoxetine\u2019s loss of efficacy<\/p>\n
Two influential reviews published in 2016 and 2020 in prestigious Lancet journals [1,2]<\/a> report that \u201cFor efficacy, only fluoxetine was statistically significantly more effective than placebo (standardised mean difference [SMD] -0.51, 95% credible interval [CrI] -0.99 to -0.03).\u201d [1]<\/a><\/p>\n The authors of the 2016 review concluded that \u201cwhen considering the risk\u2013benefit profile of antidepressants in the acute treatment of major depressive disorder, these drugs do not seem to offer a clear advantage for children and adolescents. Fluoxetine is probably the best option to consider when a pharmacological treatment is indicated.\u201d [1]<\/a><\/p>\n Based on these findings, major guidelines recommend fluoxetine as the first-line antidepressant for treating pediatric depression [3]<\/a>. However, in 2021, a review from the prestigious Cochrane Collaboration [4]<\/a> reported only half of the efficacy of the 2016 and 2020 reviews, and with much greater precision: SMD = -0.20 (95% CI -0.28 to -0.11). Furthermore, the quality of the evidence in the Cochrane review was rated as \u201cmoderate,\u201d in contrast to the Lancet reviews, which reported a \u201clow certainty.\u201d<\/p>\n Fluoxetine can now be considered clinically equivalent to placebo, with a drug-placebo difference of only -2.8 points on the Childhood Depression Rating scale (CDRS-R) which has a range from 17 to 113 (Fig. 1). The Cochrane review concluded that \u201cmost newer antidepressants may be associated with small and unimportant reductions in depression symptoms compared with placebo, which raises the question of whether they should be used at all.\u201d Interestingly, neither the Cochrane authors nor most treatment guidelines addressed the loss of efficacy.<\/p>\n Our attempts to explain the loss of fluoxetine\u2019s efficacy<\/p>\n Our initial hypothesis was that there were weaker effects in more recent trials due to a phenomenon known as the \u201cnovelty bias.\u201d Indeed, our own meta-analysis provided evidence for this [3]<\/a> (Fig. 2).<\/p>\n Upon further investigation, we discovered that the Lancet reviews included a small fluoxetine trial with an extremely large effect size (SMD >4) which is highly improbable in medicine. We identified severe problems with this trial and concluded that it is an untrustworthy \u201czombie\u201d trial. Next, we aimed to reproduce the Lancet reviews and the impact of the zombie trial. When we excluded the zombie, the efficacy of fluoxetine in the Lancet reviews decreased from SMD -0.51 to SMD -0.26 and -0.29. These results were comparable to our reanalysis of the Cochrane review (SMD -0.27). Our findings were rejected by five journals but a preprint is available [5]<\/a> and, after the five rejections, it will soon be published in a journal.<\/p>\n Why can a treatment lose its efficacy?<\/p>\n Our meta-analysis revealed that estimates of fluoxetine\u2019s efficacy decreased over time, regardless of the zombie trial (Fig. 2). This finding aligns with the novelty bias, a well-known and widespread phenomenon in medicine. Several methodological biases and problematic research practices can explain the novelty bias.<\/p>\n Preregistration, reporting bias, and outcome switching<\/p>\n Earlier trials were conducted before registration and reporting of trials became mandatory. From around 2000 onwards, depending on the field and guidelines, trials have had to be pre-registered. This prevents the study methodology and data analysis from being changed post-hoc to produce more favorable results and ensures that studies with unfavorable results are not left unreported. Figure 3 illustrates the dramatic impact of mandatory registration and reporting. Before mandatory registration, most of the published research findings were positive; afterwards positive trials became the exception.<\/p>\n A 2008 review of antidepressant trials, most of which were conducted before mandatory registration, reported that nearly all failed trials were unpublished [6]<\/a>. Due to mandatory registration, an increasing number of negative studies have come to light, resulting in a decline in efficacy over time. This likely applies to the database on pediatric antidepressants as well. Indeed, Eli Lilly\u2019s first pediatric fluoxetine trial from 1986 was negative and was never published [7]<\/a>.<\/p>\n Sponsorship Bias<\/p>\n Another important potential mechanism that can explain the decline in efficacy estimates is sponsorship bias. When a new drug is introduced, trials are usually conducted and sponsored by the manufacturer of the drug. For example, Eli Lilly, the manufacturer of fluoxetine, sponsored the two early trials published in 1997 and 2002 [8,9]<\/a>. Neither trial was pre-registered. A third influential early trial was Treatment of Adolescent Depression Study (TADS), which was publicly funded; however, most of the authors had financial ties to Eli Lilly, so this study can hardly be considered independent. All three trials reported statistically and probably clinically significant results for fluoxetine (see Fig. 2). Later trials were mostly conducted by competing companies, using fluoxetine as an established comparator drug. In these trials, fluoxetine\u2019s efficacy was much smaller and often failed to be statistically significant.<\/p>\n Unblinding and expectancy effects<\/p>\n The decrease in efficacy may be attributed to biases related to expectations and unblinding. Fluoxetine was one of the first SSRIs studied for pediatric depression. It was already a blockbuster drug for adults and was considered safer and better tolerated than previous antidepressants. Consequently, high expectations were placed on fluoxetine when it was initially studied in young patients [10]<\/a>. Such expectations can bias trial results. A recent reanalysis of the TADS trial revealed that patients, their parents, clinicians, and even independent (blinded) evaluators could guess better than chance who was treated with fluoxetine or placebo [11]<\/a>. The study also demonstrated the impact of expectancy: there was a difference of 10 CDRS-R points (SMD = 0.7) between those who thought they were on fluoxetine versus those who thought they were on placebo. In contrast, there was only a small difference between those who were actually on fluoxetine or placebo (difference of 2.7 points, SMD = 0.2). Actual treatment allocation could not significantly predict treatment outcome variance above that explained by correct guessing. Importantly, these findings contradict the claim that study participants are unblinded because the drug is effective.<\/p>\n The impact of unblinding may be reduced by decreasing the probability of receiving placebo, such as in multi-arm trials. In more recent trials with multiple arms it has become more difficult to guess exactly which group one is in. Consistent with this assumption, efficacy estimates were substantially higher in the subset of trials with only a 50% chance of receiving placebo (SMD 0.22) than in all trials (SMD 0.12) [12]<\/a>. Furthermore, positive expectations about the effectiveness of SSRIs have likely decreased due to growing concerns about their efficacy and potential risks, such as increased suicidality.<\/p>\n What we may learn from dropout rates<\/p>\n The aforementioned biases can also impact dropout rates. As a participant in a trial of a promising new drug, you may be disappointed if you end up in the placebo group. You may be able to guess this because of a lack of effects, which may lead you to leave the study. Experiencing adverse events can also lead to dropping out. Therefore, dropout rates can be used to evaluate the acceptability of treatments and their overall harm-benefit ratio [13]<\/a>. If a treatment is safe and effective, there should be fewer dropouts in the treatment group than in the placebo group.<\/p>\n I conducted meta-analysis\/regression analyses that revealed changes in dropout rates in fluoxetine trials over time (Fig. 4). In earlier trials, fewer patients dropped out of the drug arms than the placebo arms, but this trend is not evident in more recent trials.<\/p>\n Furthermore, when fluoxetine was the experimental drug compared only to placebo, there were fewer dropouts in the drug arms than in the placebo arms (Fig. 5). In contrast, when fluoxetine was the comparator drug alongside a more novel drug, the dropout rates of fluoxetine and placebo were similar. Therefore, these results again suggest that fluoxetine is no longer more acceptable than placebo in recent trials.<\/p>\n To my knowledge, no one has investigated whether similar biases found for fluoxetine have affected the efficacy estimates of other antidepressants. Now, let us examine the characteristics of placebo-controlled trials of three commonly used antidepressants: sertraline, citalopram, and escitalopram (Table 1). None of the trials included another antidepressant for comparison and all were sponsored by the manufacturer. Only one trial was registered and only one trial was not rated as having a high risk of bias in the Cochrane review. Therefore, these trials are likely affected by the same biases as observed in early fluoxetine trials. Nonetheless, most trials were negative and had small effects. Overall, none of the drugs were statistically significant in the Lancet reviews. In the Cochrane review, only sertraline was statistically significant, but we could not reproduce this finding.<\/p>\n Table 1. Characteristics of clinical trials and meta-analytic results.<\/p>\n Drug\/Study Sertraline<\/p>\n \u00a0\u00a0\u00a0 Wagner 2003a \u00a0\u00a0\u00a0 Wagner 2003a \u00a0\u00a0\u00a0 NMA Zhou 2020<\/p>\n -0.11 (-0.71 to 0.49)<\/p>\n \u00a0\u00a0\u00a0 NMA Hetrick 2021a<\/p>\n -3.51 (-6.99 to -0.04)b Citalopram<\/p>\n \u00a0\u00a0\u00a0 Wagner 2004 \u00a0\u00a0\u00a0 von Knorring 2006 \u00a0\u00a0\u00a0 NMA Zhou 2020<\/p>\n -0.18 (-0\u00b789 to 0.55)<\/p>\n \u00a0\u00a0\u00a0 NMA Hetrick 2021a<\/p>\n -2.90 (-8.23 to 2.43)b<\/p>\n -0.35 (-0.71 to 0.02)<\/p>\n Escitalopram<\/p>\n \u00a0\u00a0\u00a0 Wagner 2006 \u00a0\u00a0\u00a0 Emslie 2009 \u00a0\u00a0\u00a0 NMA Zhou 2020<\/p>\n -0.17 (-0.88 to 0.54)<\/p>\n \u00a0\u00a0\u00a0 NMA Hetrick 2021a<\/p>\n -2.62 (-2.62 to 0.04)b<\/p>\n -0.17 (-0.39 to 0.05)<\/p>\n aSMDs from the Cochrane review are from our reproduction because they did not report SMDs. The Lancet\u00a0 review (Zhou et al., 2020) included trials with any depression measure and included psychotherapy trials, too. The Cochrane review only included drug trials and only those with the CDRS-R as outcome. bCDRS-R points. cSelective reporting. dOther ROB. eAttrition bias. Abbreviations: NMA: network meta-analysis. ROB: Risk of Bias.<\/p>\n Dropout rates were numerically lower in the placebo arms than in the drug arms in all but one trial (Table 2). This suggests that, when considering overall dropout as a combined measure of efficacy and safety, these three antidepressants were comparable or inferior to treatment with a placebo.<\/p>\n Table 2. Dropout rates in the trials for sertraline, citalopram and escitalopram<\/p>\n Dropout<\/p>\n Drug\/Study Sertraline<\/p>\n \u00a0\u00a0\u00a0 Wagner 2003a (33.0%)<\/p>\n 14\/91<\/p>\n (15.3%)<\/p>\n \u00a0\u00a0\u00a0 Wagner 2003a (15.2%)<\/p>\n 17\/96<\/p>\n (17.7%)<\/p>\n \u00a0\u00a0\u00a0 Both combined Citalopram<\/p>\n \u00a0\u00a0\u00a0 Wagner 2004 \u00a0\u00a0\u00a0 von Knorring 2006 (35.7%)<\/p>\n Escitalopram<\/p>\n \u00a0\u00a0\u00a0 Wagner 2006 \u00a0\u00a0\u00a0 Emslie 2009 \u00a0<\/p>\n Professional ignorance of these findings<\/p>\n First, our review of major treatment guidelines published or updated after the Cochrane review was published revealed that the reduced efficacy of fluoxetine has not been adequately acknowledged and fluoxetine continues to be recommended as a first-line antidepressant for pediatric depression [3]<\/a>.<\/p>\n Second, some key opinion leaders (KOLs) argue that older trials are less biased [14]<\/a>. For example they argue that earlier trials were conducted in fewer and more experienced study centers, resulting in higher quality. However, we could not find evidence for these arguments in the fluoxetine database [15]<\/a>. Furthermore, these KOLs ignore the fact that single-center trials can be affected by researcher bias and should therefore be interpreted cautiously [16]<\/a>. Indeed, older fluoxetine trials from single or few centers were rated as being at high risk of bias, according to the Lancet and Cochrane reviews [1,2,4]<\/a>.<\/p>\n Third, there was a scientifically problematic shift back to relying solely on statistical significance while ignoring the lack of clinically meaningful effects. The Cochrane review concluded that \u201cmost newer antidepressants may be associated with small and unimportant reductions in depression symptoms compared with placebo, which raises the question of whether they should be used at all.\u201d However,\u00a0 based on significant (or nearly significant) findings, they also concluded that \u201cif medications are to be used, there is evidence to support a greater range of options for first-line prescribing of antidepressants including sertraline, escitalopram, duloxetine as well as fluoxetine to guideline recommendations that recommend fluoxetine alone (NICE 2019).\u201d<\/p>\n This conclusion was uncritically adopted in the German guidelines from 2025 [17]<\/a>, which recommended the use of fluoxetine, sertraline, and escitalopram for moderate to severe depression. It is argued that there is \u201cstrong evidence\u201d for these drugs. Contrast this with the actual finding in the Cochrane review: \u201cthere was probably a small unimportant difference between the following NGAs and placebo [sertraline, fluoxetine, escitalopram].\u201d [Emphasis mine.] It seems that the guideline panel simply equated statistical significance with \u201ca strong evidence base,\u201d while disregarding the clinical unimportance of the effects. Furthermore, the findings from the previous Lancet reviews were ignored. These reviews did not find even statistically significant effects for sertraline or escitalopram.<\/p>\n Fourth, the novelty bias has been completely ignored in the interpretation of the findings for antidepressants other than fluoxetine. Commonly used SSRIs, such as escitalopram and sertraline,\u00a0 were investigated a long time ago, without mandatory registration, and almost exclusively by the drug companies. These drugs were never tested by competing companies or independent organizations. Consequently, the efficacy of these drugs is likely overestimated.<\/p>\n Fifth, the concerning results regarding dropout are not acknowledged. If a drug is effective and well tolerated, there should be a lower dropout rate in the drug arms compared to the placebo arms. However, this was only observed in early fluoxetine trials, likely due to methodological biases. For other antidepressants, dropout rates are numerically lower in the placebo arms, despite the methodological biases favoring the drugs.<\/p>\n Finally, the sobering results of independent reanalyses have not been adequately acknowledged. The most prominent example is Study 329, in which paroxetine was deemed \u201cgenerally well tolerated and effective\u201d [18]<\/a>. However, independent researchers revealed that paroxetine was not superior to placebo and that there was a significant increase in suicidal events with paroxetine use [19]<\/a>.<\/p>\n A reanalysis of the two early fluoxetine trials (Emslie 1997, 2002) [20]<\/a> found that \u201cEssential information was missing and there were unexplained numerical inconsistencies. (1) The efficacy outcomes were biased in favour of fluoxetine by differential dropouts and missing data. The efficacy on the Children\u2019s Depression Rating Scale-Revised was 4% of the baseline score, which is not clinically relevant. Patient ratings did not find fluoxetine effective. (2) Suicidal events were missing in the publications and the study reports. Precursors to suicidality or violence occurred more often on fluoxetine than on placebo.\u201d<\/p>\n A recent reanalysis [21]<\/a> of the influential TADS study concluded that \u201cIn contrast to the original TADS Team\u2019s reporting, there was a higher level of harm uncovered in allocation groups taking fluoxetine, including 11 unreported suicide-related adverse events.\u201d<\/p>\n Another example is the reanalysis of the CIT-MD-18 study on citalopram [22]<\/a>. It was revealed that the publication was ghost-written and that \u201cthe published article contained efficacy and safety data inconsistent with the protocol criteria. Procedural deviations went unreported imparting statistical significance to the primary outcome, and an implausible effect size was claimed; positive post hoc measures were introduced and negative secondary outcomes were not reported; and adverse events were misleadingly analysed.\u201d<\/p>\n In their conclusion, the authors of the TADS reanalysis stated that \u201cThe findings of this as well as several other reanalyses suggest that antidepressant trial results cannot be taken at face value\u201d [21]<\/a>. Evidence syntheses and treatment guidelines generally lack this justified scepticism.<\/p>\n Consequences for the harm-benefit assessment<\/p>\n Evidence from clinical trials suggests that all antidepressants investigated for treating pediatric depression can be considered clinically equivalent to placebo. This is especially true when considering the biases revealed in the analysis of fluoxetine trials, which were ignored when interpreting the evidence for other antidepressants. Consequently, even minor adverse events can lead to an unfavorable harm-benefit ratio. Adverse events that occur more frequently during treatment with SSRIs than placebo include sexual dysfunction, gastrointestinal problems, insomnia, and suicidality. Therefore, the harm-benefit ratio is problematic for many patients. Unfortunately, current treatment recommendations and clinical practices are based on an uncorrected, uncritical interpretation of the evidence, which can harm patients. Necessary corrections are overdue.<\/p>\n 1 <\/a>\u00a0\u00a0 Cipriani A, Zhou X, Del Giovane C, <\/a>et al.<\/a> Comparative efficacy and tolerability of antidepressants for major depressive disorder in children and adolescents: a network meta-analysis. <\/a>The Lancet<\/a>. 2016;388:881\u201390. doi: 10.1016\/S0140-6736(16)30385-3 <\/a><\/p>\n 2 <\/a>\u00a0\u00a0 Zhou X, Teng T, Zhang Y, <\/a>et al.<\/a> Comparative efficacy and acceptability of antidepressants, psychotherapies, and their combination for acute treatment of children and adolescents with depressive disorder: a systematic review and network meta-analysis. <\/a>Lancet Psychiatry<\/a>. 2020;7:581\u2013601. doi: 10.1016\/S2215-0366(20)30137-1 <\/a><\/p>\n 3 <\/a>\u00a0\u00a0 Pl\u00f6derl M, Lyus R, Horowitz MA, <\/a>et al.<\/a> The loss of efficacy of fluoxetine in pediatric depression: explanations, lack of acknowledgment, and implications for other treatments. <\/a>J Clin Epidemiol<\/a>. 2026;189:112016. doi: 10.1016\/j.jclinepi.2025.112016 <\/a><\/p>\n 4 <\/a>\u00a0\u00a0 Hetrick SE, McKenzie JE, Bailey AP, <\/a>et al.<\/a> New generation antidepressants for depression in children and adolescents: a network meta-analysis. <\/a>Cochrane Database Syst Rev<\/a>. 2021;2021. doi: 10.1002\/14651858.CD013674.pub2 <\/a><\/p>\n 5 <\/a>\u00a0\u00a0 Lyus R, Naudet F, van Valkenhoef G, <\/a>et al.<\/a> A Re-Appraisal of Three Network Meta-Analyses to Explain the Discrepancy in Findings for the Efficacy of Fluoxetine for the Treatment of Depression in Children and Adolescents. <\/a>medRxiv<\/a>. 2025;2025.09.07.25334757. doi: 10.1101\/2025.09.07.25334757 <\/a><\/p>\n 6 <\/a>\u00a0\u00a0 Turner EH, Matthews AM, Linardatos E, <\/a>et al.<\/a> Selective publication of antidepressant trials and its influence on apparent efficacy. <\/a>N Engl J Med<\/a>. 2008;358:252\u201360. doi: 10.1056\/NEJMsa065779 <\/a><\/p>\n 7 <\/a>\u00a0\u00a0 Eli Lilly. Clinical Study Summary: Study B1Y-MC-HCCJ. 1986. <\/a><\/p>\n 8 <\/a>\u00a0\u00a0 Emslie GJ, Rush AJ, Weinberg WA, <\/a>et al.<\/a> A double-blind, randomized, placebo-controlled trial of fluoxetine in children and adolescents with depression. <\/a>Arch Gen Psychiatry<\/a>. 1997;54:1031\u20137. doi: 10.1001\/archpsyc.1997.01830230069010 <\/a><\/p>\n 9 <\/a>\u00a0\u00a0 Emslie GJ, Heiligenstein JH, Wagner KD, <\/a>et al.<\/a> Fluoxetine for Acute Treatment of Depression in Children and Adolescents: A Placebo-Controlled, Randomized Clinical Trial. <\/a>J Am Acad Child Adolesc Psychiatry<\/a>. 2002;41:1205\u201315. doi: 10.1097\/00004583-200210000-00010 <\/a><\/p>\n 10 <\/a> Boussageon R, Gougeon A, Kassa\u00ef B. Some additional considerations on the evidence for fluoxetine in pediatric depression. <\/a>J Clin Epidemiol<\/a>. 2026;112137. doi: 10.1016\/j.jclinepi.2026.112137 <\/a><\/p>\n 11 <\/a> Jureidini J, Moncrieff J, Klau J, <\/a>et al.<\/a> Treatment guesses in the Treatment for Adolescents with Depression Study: Accuracy, unblinding and influence on outcomes. <\/a>Aust N Z J Psychiatry<\/a>. 2024;58:355\u201364. doi: 10.1177\/00048674231218623 <\/a><\/p>\n 12 <\/a> Feeney A, Hock RS, Fava M, <\/a>et al.<\/a> Antidepressants in children and adolescents with major depressive disorder and the influence of placebo response: A meta-analysis. <\/a>J Affect Disord<\/a>. 2022;305:55\u201364. doi: 10.1016\/j.jad.2022.02.074 <\/a><\/p>\n 13 <\/a> Sharma T, Guski LS, Freund N, <\/a>et al.<\/a> Drop-out rates in placebo-controlled trials of antidepressant drugs: A systematic review and meta-analysis based on clinical study reports. <\/a>Int J Risk Saf Med<\/a>. 2019;30:217\u201332. doi: 10.3233\/JRS-195041 <\/a><\/p>\n 14 <\/a> Walkup JT, Strawn JR. Depressive disorders in children and adolescents. In: Thapar A, Pine DS, Cortese S, <\/a>et al.<\/a>, eds. <\/a>Rutter\u2019s Child and Adolescent Psychiatry and Psychology<\/a>. Wiley 2025:898\u2013914. <\/a><\/p>\n 15 <\/a> Pl\u00f6derl M, Lyus R, Naudet F. Can fluoxetine\u2019s diminished efficacy in pediatric depression be explained by study sites, baseline severity, age, and psychological interventions? A secondary exploratory meta-regression. <\/a>J Psychiatr Res<\/a>. 2026;202:160\u20133. doi: 10.1016\/j.jpsychires.2026.08.018 <\/a><\/p>\n 16 <\/a> Unverzagt S, Prondzinsky R, Peinemann F. Single-center trials tend to provide larger treatment effects than multicenter trials: a systematic review. <\/a>J Clin Epidemiol<\/a>. 2013;66:1271\u201380. doi: 10.1016\/j.jclinepi.2013.05.016 <\/a><\/p>\n 17 <\/a> Kloek M, Zsigo C, Klingele C, <\/a>et al.<\/a> S3-Leitlinie Behandlung von depressiven St\u00f6rungen bei Kindern und Jugendlichen. Deutsche Gesellschaft f\u00fcr Kinder- und Jugendpsychiatrie, Psychosomatik und Psychotherapie e.V. (DGKJP) 2025. <\/a><\/p>\n 18 <\/a> Keller MB, Ryan ND, Strober M, <\/a>et al.<\/a> Efficacy of Paroxetine in the Treatment of Adolescent Major Depression: A Randomized, Controlled Trial. <\/a>J Am Acad Child Adolesc Psychiatry<\/a>. 2001;40:762\u201372. doi: 10.1097\/00004583-200107000-00010 <\/a><\/p>\n 19 <\/a> Le Noury J, Nardo JM, Healy D, <\/a>et al.<\/a> Restoring Study 329: efficacy and harms of paroxetine and imipramine in treatment of major depression in adolescence. <\/a>BMJ<\/a>. 2015;h4320. doi: 10.1136\/bmj.h4320 <\/a><\/p>\n 20 <\/a> G\u00f8tzsche PC, Healy D. Restoring the two pivotal fluoxetine trials in children and adolescents with depression. <\/a>Int J Risk Saf Med<\/a>. 2022;33:385\u2013408. doi: 10.3233\/JRS-210034 <\/a><\/p>\n 21 <\/a> Aboustate N, Jureidini J, Woodman R, <\/a>et al.<\/a> Restoring TADS: RIAT reanalysis of the Treatment for Adolescents with Depression Study. <\/a>Int J Risk Saf Med<\/a>. 2025;9246479251337879. doi: 10.1177\/09246479251337879 <\/a><\/p>\n 22 <\/a> Jureidini JN, Amsterdam JD, McHenry LB. The citalopram CIT-MD-18 pediatric depression trial: Deconstruction of medical ghostwriting, data mischaracterisation and academic malfeasance. <\/a>Int J Risk Saf Med<\/a>. 2016;28:33\u201343. doi: 10.3233\/JRS-160671 <\/a><\/p>\n ***<\/p>\n Mad in America hosts blogs by a diverse group of writers. These posts are designed to serve as a public forum for a discussion\u2014broadly speaking\u2014of psychiatry and its treatments. The opinions expressed are the writers\u2019 own.<\/p>\n","protected":false},"excerpt":{"rendered":"Fluoxetine is recommended as a first-line antidepressant to treat pediatric depression in major guidelines, and it is one…\n","protected":false},"author":2,"featured_media":616299,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[303622,56463,303623,219396,134,111,139,69,40332,303624,61770,303625],"class_list":["post-616298","post","type-post","status-publish","format-standard","has-post-thumbnail","category-health","tag-antidepressant-efficacy","tag-antidepressants","tag-antidepressants-and-children","tag-fluoxetine","tag-health","tag-new-zealand","tag-newzealand","tag-nz","tag-prozac","tag-ssri-efficacy","tag-ssris","tag-ssris-and-children"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts\/616298","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/comments?post=616298"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts\/616298\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/media\/616299"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/media?parent=616298"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/categories?post=616298"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/tags?post=616298"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"](\"https:\/\/www.newsbeep.com\/nz\/wp-content\/uploads\/2026\/09\/Figure1.jpg\")
<\/a><\/p>\n![\"\"](\"https:\/\/www.newsbeep.com\/nz\/wp-content\/uploads\/2026\/09\/Figure2.jpg\")
<\/a>Figure 2.\u00a0 Efficacy of fluoxetine over time (figure is from [3]). Error-bars correspond to the 95% confidence interval (CI). The dot-dashed gray line is the result of the meta-analytic aggregation of the studies over time, together with the 95% CI-Band shaded in gray. The horizontal dashed gray line is the threshold of clinical significance.However, we found that the overall efficacy estimates had already stabilized by 2014. Therefore, much smaller effects should have emerged by the time the two Lancet reviews were published in 2016 and 2020. Consequently, the inclusion of more recent trials was an insufficient explanation for the discrepancies between the review\u2019s findings.<\/p>\n![\"\"](\"https:\/\/www.newsbeep.com\/nz\/wp-content\/uploads\/2026\/09\/Figure.3.jpg\")
<\/a>Figure 3. Taken from https:\/\/www.clinicaltrialsabundance.blog\/p\/clinical-trial-reforms-that-once<\/p>\n![\"\"](\"https:\/\/www.newsbeep.com\/nz\/wp-content\/uploads\/2026\/09\/Figure4.jpg\")
<\/a>Figure 4. Dropout rates in the fluoxetine-arms versus the placebo arms over time. Risk-ratios smaller than one indicate lower dropout rates in the fluoxetine arm compared to the placebo arm. The line denotes the regression line.<\/p>\n![\"\"](\"https:\/\/www.newsbeep.com\/nz\/wp-content\/uploads\/2026\/09\/Figure5.jpg\")
<\/a>Figure 5. Dropout rates in trials where fluoxetine was the experimental drug (only compared with placebo) or used as comparator drug alongside a novel drug and placebo.
\nImplications for other antidepressants<\/p>\n
\nRegistered
\nSponsored
\nCompared with
\nOutcome
\nPositive trial?
\nhigh ROB?<\/p>\n
\nNo
\nYes
\nPlacebo only
\n-0.25 (-0.51 to 0.01)
\nno
\nyesc,d<\/p>\n
\nNo
\nYes
\nPlacebo only
\n-0.20 (-0.45 to 0.05)
\nno
\nyesc,d<\/p>\n
-0.23 (-0.48 to 0.02)<\/p>\n
\nNo
\nYes
\nPlacebo only
\n-0.34 (-0.61 to -0.09)
\nyes\/no
\nyes c,e<\/p>\n
\nNo
\nYes
\nPlacebo only
\n-0.01 (-0.25 to 0.24)
\nno
\nyes c,e<\/p>\n
\nNo
\nYes
\nPlacebo only
\n-0.13 (-0.34 to 0.08)
\nno
\nno<\/p>\n
\nYes
\nYes
\nPlacebo only
\n-0.21 (-0.40 to -0.02)
\nyes
\nyes c<\/p>\n
\nDrug
\nPlacebo<\/p>\n
\n32\/97<\/p>\n
\n14\/92<\/p>\n
\n46\/189 (24.3%)
\n31\/187 (16.6%)<\/p>\n
\n22\/93
(23.7%)
\n18\/85
(21.2%)<\/p>\n
\n45\/124 (36.3%)
\n46\/120<\/p>\n
\n30\/132 (22.7%)
\n21\/136 (15.4%)<\/p>\n
\n32\/158 (20.3%)
\n25\/158 (15.8%)<\/p>\n