PONE-D-22-10307The effect of antidepressants on severity of COVID-19 in hospitalized patients:

A systematic review and meta-analysisPLOS ONE

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1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This article, which attempts a meta-analysis of the preventive effect of antidepressants on COV-19 infections, should be rejected for the following reasons.

1. There are already meta-analysis papers showing the efficacy of fluvoxamine for COVID-19 (PMID: 35385087, 35383578).

2. Only three RCTs could be used for the meta-analysis, although 12 articles with a variety of methods, including RCTs and case-control, observational studies, were extracted. The results are not clinically useful information because of the varied treatment settings and severity of illness of the subjects. Ultimately, this indicates that the number of papers is still insufficient for a meta-analysis on this topic.

Reviewer #2: This is a review of the manuscript “The effect of antidepressants on severity of COVID-19 in hospitalized patients: A systematic review and meta-analysis” submitted for publication in PLOS One. This is a very interesting manuscript, which addresses a timely and important research question, with potential important therapeutic implications. Below are several comments and suggestions to strengthen the submission that I hope the authors will find useful.

1/ Since the literature on this topic is progressing fastly, this meta-analysis would benefit in being actualized, until June 2022 for example. This would be particularly important since a very large observational study, including fluoxetine, has been released in March 2022 (doi: 10.1093/ofid/ofac156. PMID: 35531374).

2/ I would discuss the exclusion from the meta-analysis of studies not reporting how COVID-19 was assessed. If it was clinically or if the study is based on EHR data, it constitutes a major bias as patients may reach the outcome (e.g. death or hospitalization) for another reason.

3/ As indicated in the introduction, the severity of COVID-19 is known to be higher in patients with medical comorbidities, and people taking antidepressants, mainly because they suffer from major depression or anxiety disorders, are more likely to have medical comorbidities than their counterparts. Therefore, studies not taking into account of baseline comorbidities, indication of the treatment (i.e., depressive disorder, anxiety disorder, dementia, neurologic pain), or baseline severity in their analyses are likely to provide biased estimates, as recently shown (doi: 10.1038/s41380-021-01393-7. PMID: 34837060; doi: 10.1016/j.bpsgos.2021.12.007. PMID: 35013734).

Therefore, for observational studies and case-control studies, I would recommend to also extract data on medical comorbidities (whether analyses of each study took into account them and how), medical indication, and clinical severity at baseline, to help judge the readers the quality of each study. Studies without randomization not properly adjusting for comorbidities and age, the 2 main risk factors for severe COVID-19, cannot be considered at low risk of bias. These data may also reveal a clear source of heterogeneity of results across studies if only studies not adjusting for comorbidities do not find significant protective associations.

4/ Study period and country, allowing to approximate the dominant variant at the time of each study, may be also worth to be included, to examine whether the effect of antidepressants may apply across all variants.

5/ Importantly, I think it would be interesting and important to present in this article a metanalysis of observational studies, 1 for any antidepressant or SSRIs, and 1 for each molecule for which there are for example at least 3 different studies (e.g., fluoxetine), by including calculated effect size (expressed as SMD for example) of each study based on adjusted results (e.g. AOR). Alternatively or additionally, a meta-analysis including only matched observational data can be performed. It would give a sense of the magnitude of the effect and of the heterogeneity of the results. A global estimate of the effect of antidepressants would strongly increase the interest for this article.

6/ To understand conflicting results across studies, I would recommend performing sensitivity analyses: 1) excluding studies not reporting how COVID-19 was detected (i.e., without specifying if individuals had a positive RT-PCR or antigen test) if not already excluded (see comment #1); 2) excluding studies not taking into account baseline comorbidities as it is a central confounding factor associated with both antidepressant use and COVID-19-related outcomes, 3) excluding studies not reporting the dose of antidepressant, as these studies may have included in their analyses from EHR individuals who had a past but not a current prescription of antidepressant (providing the dose of antidepressant is a way for increasing the confidence that the patient actually received the treatment at the time of the infection in such study), and 4) keeping only truly “high-quality” / “at low-risk of bias” studies not excluded in 1), 2), and 3).

Furthermore, only the observational studies kept in 4) can be considered at low risk of bias; to the reviewer’s point of view, a study in which (i) COVID-19 status is uncertain in the absence of a specific test, (ii) compared groups are not adequately balanced in terms of medical comorbidities by an adequate adjustment, and (iii) there is uncertainty whether the patients actually took the treatment given the absence of information on the dose, cannot be considered at low risk of bias, contrary to what is indicated in L171 of the manuscript. This information should also be detailed in the result section.

A significant pooled association in the last sensitivity analysis of studies with low-risk of bias would give strength to the putative conclusion that higher-quality studies converge in finding significant protective effect of antidepressants, whereas lower-quality studies (with substantial risk of bias) find either a non-significant or a deleterious effect of antidepressants.

7/ I’m surprised by the presence of “unclear” for the Reis et al. study in the Table 4. The multi-arm RCT TOGETHER trial design seems to be of high quality, but maybe the unclear information can be found on the website https://www.togethertrial.com/trial-specifications. I tend to think that this study should be added to “the exceptions” L173.

8/ L240: The primary outcome of the Reis et al. study was “as a composite endpoint of hospitalisation defined as either retention in a COVID-19 emergency setting or transfer to tertiary hospital due to COVID-19” (the study was stopped for superiority for the primary outcome). In a separate letter (see Author's reply. Lancet Glob Health. 2022 Mar;10(3):e333), the main authors indicate that the outcome (hospitalisation or emergency care >24 h) and the outcome for FDA criterion for severe COVID-19 (used by the FDA to approve molnupiravir and Paxlovid) was also significant. In addition, the per-protocol analysis indicates a significant reduction in mortality [OR 0·09; 95% CI 0·01–0·47], and there were no differences in number of treatment emergent adverse events or drug–drug interactions. I think this information is important to be specified, before presenting secondary outcomes, for which the study was not powered. In addition, in the pooled RR for clinical trials, I think that the result of the primary outcome should be better used, and that a separate sensitivity analysis within the same Figure including the result of the per-protocol analysis for the main outcome of the Reis et al. study would give a better sense of the true effect size of fluvoxamine.

9/ L245. Similarly, the result for the main outcome of the Calusic et al study should be clearly indicated before presenting secondary outcomes, for which the study was not powered.

10/ L266: “One study proposed that antidepressants such as SSRIs and TCAs increase the risk of severe COVID-19 due to their anticholinergic effect that is likely to cause pneumonia”. This sentence should be balanced by the fact that this study (McKeigue et al.) did not specify how COVID-19 was ascertained, did not adjust for comorbidities and medical indication (to correct if true in the Table 3), and did not indicate the dose used, and, therefore, should be considered at high risk of bias.

11/ Tables 2 and 6: In the Hoertel et al. study, confounding factors (i.e., medical comorbidities, age, sex, medical indication, clinical and biological baseline severity) were identified and adjusted for. In addition, doses of each antidepressant are indicated in the Supplementary Table 1 of the article (e.g., fluoxetine 20 mg per day). Tables 2 and 6 should be corrected accordingly.

12/ L307: I suggest to revise the following sentence « This could explain the findings of Hoertel et al. study (8), although considering that there are other drugs such as chlorpromazine with ASM inhibition activity that didn’t show the same protective effects on mortality in COVID-19 patients, this mechanism is unlikely a major factor for said effect”, which sounds speculative.

Indeed, effect on ASM of a medication in a patient is likely to depend on (i) the magnitude of the in vitro effect of the ASM (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3166082/), (ii) the dose prescribed, and (iii) the concentration in the lungs (https://f1000research.com/articles/10-477).

In the cited study on chlorpromazine, the mean dose was low (e.g., 70 mg/d) and the in vitro inhibition of ASM of chlorpromazine is far lower than that of fluoxetine and fluvoxamine (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3166082/).

Rather, several studies preclinical (in vitro and ex vivo) and observational studies suggest that inhibition of acid sphingomyelinase/ceramide system plays a potentially important role and may explain both potential antiviral and anti-inflammatory effects of certain antidepressants in Covid (doi: 10.1038/s41380-021-01254-3; doi: 10.1016/j.jbc.2021.100701). Particularly, among SSRIs, the magnitude of the in vitro inhibition of ASM, which varies across molecules (eg, fluoxetine > paroxetine > fluvoxamine > other SSRIs) (doi: 10.1371/journal.pone.0023852), appears to correlate with the magnitude of the in vitro antiviral effect against SARS-CoV-2 (doi: 10.1080/22221751.2020.1829082; doi: 10.1001/jamanetworkopen.2021.36510). Furthermore, a retrospective cohort study of an adult psychiatric facility operated by the New York State Office of Mental Health found a significant and substantial protective association between the use of antidepressants, and particularly fluoxetine and trazodone, and COVID-19 infection (doi: 10.1192/bjo.2021.1053). In addition, a recent study found that patients taking a FIASMA antidepressant at baseline had a significantly reduced risk of intubation or death compared with those taking a non-FIASMA antidepressant at baseline, adjusting for sociodemographic characteristics, psychiatric and other medical comorbidity, and other medications (doi: 10.1038/s41398-022-01804-5. PMID: 35241663). Finally and importantly, four studies found that plasma ceramide levels strongly correlate with clinical and inflammation severity among patients with Covid-19 (DOI: 10.1038/s41598-021-00286-7; DOI: 10.3390/ijms221910198; DOI: 10.3390/ijms22094794; https://www.medrxiv.org/content/10.1101/2022.01.19.22269391v1). These data may enrich the discussion.

13/ To the reviewer’s point of view, S1R agonist effect as a central explanation of the effect of fluvoxamine remains uncertain in the absence of any preclinical or clinical data specific to Covid supporting this effect. More importantly, based on the results of this meta-analysis, it seems unable to explain associations observed between non-(or very low)-S1R antidepressants (such as paroxetine, mirtazapine or venlafaxine, which are FIASMAs (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3166082/), and reduced risk of intubation or death (doi: 10.1038/s41380-021-01021-4) as well as anti-inflammatory effects observed with a broad range of antidepressants (and not only the S1R antidepressants fluvoxamine and fluoxetine) in individuals with major depression (doi: 10.1007/s12035-017-0632-1).

14/ Beyond S1R and FIASMA potential mechanisms, anti-inflammatory properties of antidepressants might also be explained by non–S1R-inositol-requiring enzyme (IRE) pathways, such as nuclear factor κ B, inflammasomes, Toll-like receptor 4, or peroxisome proliferator-activated receptor γ (doi: 10.1001/jamanetworkopen.2021.36510; doi: 10.1038/s41380-021-01254-3).

15/ The terms “severity predictors” and “experimental studies” are confusing. I suggest to revise them as “outcomes” and “clinical trial” for example.

16/ Conclusion and abstract: Although fluvoxamine is the only antidepressant hat has been tested in RCTs against COVID, there is no observational evidence of superiority to other antidepressants; contrariwise, fluoxetine seems to be the most studied with the greatest effect size in observational studies. I think that the conclusion could include this point, which may suggest prioritizing fluoxetine and fluvoxamine in future clinical trials.

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Reviewer #1: Yes: Jun-ichi Iga

Reviewer #2: No

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The effect of antidepressants on the severity of COVID-19 in hospitalized patients:

A systematic review and meta-analysis

PONE-D-22-10307R1

Dear Dr. ZANGIABADIAN,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Robert Jeenchen Chen, MD, MPH

Academic Editor

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Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors successfully incorporated the reviewer's comments into the revised manuscript. This paper is suitable for PLOS One in the current form.

Reviewer #2: I thank the authors for their responses. The manuscript has been importantly improved.

A minor additional comment, that should not delay the publication of this important article, would be to shortly discuss the recently published RCT in the NEJM (doi:10.1056/NEJMoa2201662), that found that fluvoxamine prescribed at a low dose (100 mg/d ) to over-weighted and obese outpatients with COVID-19 showed no significant benefit on the risk of emergency department visits, hospitalizations or death, contrasting with the findings of the RCTs TOGETHER and STOP-COVID, in which fluvoxamine was prescribed at higher doses, i.e., 200 and 300 mg/d, respectively, and with results from this meta-analysis.

This discrepancy might be explained by a potential effect of fluvoxamine occurring at a minimum dose of 200 mg/d, as suggested by a recently published observational study (doi: 10.1038/s41398-022-02109-3) that found that exposure to antidepressants, especially those with FIASMA properties, was associated with reduced incidence of emergency department visitation or hospital admission among SARS-CoV-2 positive outpatients, in a dose-dependent manner and from daily doses of at least 20 mg fluoxetine equivalents. Altogether, these findings might suggest that fluvoxamine or FIASMA antidepressants should be prescribed at a minimum dose of 200 mg/d (100 mg twice daily) to possibly observe a benefit in patients with COVID-19.

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Reviewer #1: Yes: Jun-ichi Iga

Reviewer #2: No

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