<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article">
 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">
    health
   </journal-id>
   <journal-title-group>
    <journal-title>
     Health
    </journal-title>
   </journal-title-group>
   <issn pub-type="epub">
    1949-4998
   </issn>
   <issn publication-format="print">
    1949-5005
   </issn>
   <publisher>
    <publisher-name>
     Scientific Research Publishing
    </publisher-name>
   </publisher>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="doi">
    10.4236/health.2024.1611072
   </article-id>
   <article-id pub-id-type="publisher-id">
    health-137575
   </article-id>
   <article-categories>
    <subj-group subj-group-type="heading">
     <subject>
      Articles
     </subject>
    </subj-group>
    <subj-group subj-group-type="Discipline-v2">
     <subject>
      Biomedical 
     </subject>
     <subject>
       Life Sciences, Medicine 
     </subject>
     <subject>
       Healthcare
     </subject>
    </subj-group>
   </article-categories>
   <title-group>
    Cost Effectiveness of Fluvoxamine versus Desvenlafaxine among the Patients with Major Depressive Disorder in China
   </title-group>
   <contrib-group>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Jeonghoon
      </surname>
      <given-names>
       Ahn
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Soohyun
      </surname>
      <given-names>
       Noh
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff1"> 
      <sup>1</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Xueqing
      </surname>
      <given-names>
       Yang
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff2"> 
      <sup>2</sup>
     </xref>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Kyoo
      </surname>
      <given-names>
       Kim
      </given-names>
     </name> 
     <xref ref-type="aff" rid="aff3"> 
      <sup>3</sup>
     </xref>
    </contrib>
   </contrib-group> 
   <aff id="aff1">
    <addr-line>
     aDepartment of Health Convergence, Ewha Womans University, Seoul, South Korea
    </addr-line> 
   </aff> 
   <aff id="aff2">
    <addr-line>
     aAbbott Pharmaceuticals, Beijing, China
    </addr-line> 
   </aff> 
   <aff id="aff3">
    <addr-line>
     aAbbott Products Operations AG, Allschwil, Switzerland
    </addr-line> 
   </aff> 
   <pub-date pub-type="epub">
    <day>
     04
    </day> 
    <month>
     11
    </month>
    <year>
     2024
    </year>
   </pub-date> 
   <volume>
    16
   </volume> 
   <issue>
    11
   </issue>
   <fpage>
    1050
   </fpage>
   <lpage>
    1056
   </lpage>
   <history>
    <date date-type="received">
     <day>
      8,
     </day>
     <month>
      October
     </month>
     <year>
      2024
     </year>
    </date>
    <date date-type="published">
     <day>
      19,
     </day>
     <month>
      October
     </month>
     <year>
      2024
     </year> 
    </date> 
    <date date-type="accepted">
     <day>
      19,
     </day>
     <month>
      November
     </month>
     <year>
      2024
     </year> 
    </date>
   </history>
   <permissions>
    <copyright-statement>
     © Copyright 2014 by authors and Scientific Research Publishing Inc. 
    </copyright-statement>
    <copyright-year>
     2014
    </copyright-year>
    <license>
     <license-p>
      This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/
     </license-p>
    </license>
   </permissions>
   <abstract>
    <b>Objectives</b>
    <b>:</b> To estimate the cost effectiveness of fluvoxamine against desvenlafaxine in Chinese patients with major depressive disorder (MDD). 
    <b>Methods</b>
    <b>:</b> A cost effectiveness of treating Chinese patients with MDD for 6 months maintenance period has been estimated by a decision tree model. The relative effectiveness on relapse rates came from a recent network meta analysis by Kishi et al. (2023) along with local drug cost data based on WHO defined daily dose (DDD) and relapse cost for the 6 months estimated from various sources were used in the model. Based on the Quality Adjusted Life Years (QALY) gain reported by Sobocki et al. (2007), QALY loss from a relapse was estimated. Univariate sensitivity analyses were presented by a Tornado diagram and extensive probabilistic sensitivity analysis based on 10,000 simulations was performed. The most recent cost effectiveness threshold of 1.5 times GDP suggested by Cai et al. (2022) was applied. 
    <b>Results</b>
    <b>:</b> Fluvoxamine dominated desvenlafaxine (cost savings of 4003 CNY and 0.01 QALY higher in 6 months). The most sensitive parameters were relapse rates followed by desvenlafaxine cost and utility loss of relapse. However, the default result of fluvoxamine dominance was not changed for any univariate sensitivity analysis. The probabilistic sensitivity result showed the cost effectiveness acceptability at 1.5 times GDP as 99.93%. 
    <b>Conclusions</b>
    <b>:</b> The cost effectiveness of fluvoxamine against desvenlafaxine among Chinese patients with MDD in a 6-month maintenance period was cost saving with better effectiveness (i.e., dominating) with low uncertainty.
   </abstract>
   <kwd-group> 
    <kwd>
     Cost-Effectiveness Analysis (CEA)
    </kwd> 
    <kwd>
      Fluvoxamine
    </kwd> 
    <kwd>
      Desvenlafaxine
    </kwd> 
    <kwd>
      Major Depressive Disorder (MDD)
    </kwd> 
    <kwd>
      Chinese Healthcare
    </kwd>
   </kwd-group>
  </article-meta>
 </front>
 <body>
  <sec id="s1">
   <title>1. Introduction</title>
   <p>Major depressive disorder (MDD) is a psychiatric disorder characterized by at least two weeks duration of depressed mood <xref ref-type="bibr" rid="scirp.137575-1">
     [1]
    </xref>. MDD is a prevalent mental health condition, affecting 4.4% of the global population annually <xref ref-type="bibr" rid="scirp.137575-2">
     [2]
    </xref>. During the acute phase of MDD, individuals receive either pharmacological treatment, such as selective serotonin reuptake inhibitor (SSRI), or non-pharmacological interventions, including psychotherapy and electroconvulsive therapy <xref ref-type="bibr" rid="scirp.137575-3">
     [3]
    </xref> <xref ref-type="bibr" rid="scirp.137575-4">
     [4]
    </xref>. The risk of relapse or recurrence, chronicity (as indicated by the length of depressive episodes), and treatment resistance rises with each new major depressive episode <xref ref-type="bibr" rid="scirp.137575-5">
     [5]
    </xref>. Therefore, achieving full remission (typically defined as a score of 7 or lower on the 17-item Hamilton Depression Scale or a 50% - 80% reduction from the initial score) and maintaining ongoing treatment to prevent relapse or recurrence are top priorities in managing MDD <xref ref-type="bibr" rid="scirp.137575-5">
     [5]
    </xref>.</p>
   <p>A systematic review by Gu et al. <xref ref-type="bibr" rid="scirp.137575-6">
     [6]
    </xref> reported that the lifetime prevalence of MDD in China is 3.3%, and it is more prevalent in rural areas than in urban areas (2.0% vs. 1.7%) and among females than males (2.1% vs. 1.3%). The relatively low prevalence of MDD in China, estimated at 3.02%, may be attributed to the high incidence of somatic symptoms, such as headaches or stomach pain, among depressed patients <xref ref-type="bibr" rid="scirp.137575-7">
     [7]
    </xref>. These symptoms often lead to underdiagnosis, as the current diagnostic criteria primarily emphasize psychological symptoms like sadness and diminished interest and energy <xref ref-type="bibr" rid="scirp.137575-6">
     [6]
    </xref> <xref ref-type="bibr" rid="scirp.137575-8">
     [8]
    </xref>.</p>
   <p>For antidepressants, limited evidence is available among the Chinese population <xref ref-type="bibr" rid="scirp.137575-9">
     [9]
    </xref>. Hu et al. <xref ref-type="bibr" rid="scirp.137575-10">
     [10]
    </xref> projected that the total estimated cost of depression in China is 51,370 million RMB (6264 million USD) at 2002 prices. The direct cost of MDD in China was 8090 million RMB (986 million USD), while the indirect cost was 43,280 million RMB (5278 million USD). Hsieh and Qin <xref ref-type="bibr" rid="scirp.137575-11">
     [11]
    </xref> estimated that patients with depression spend annually 1836.52 CNY more on healthcare services and 3773.92 CNY more on hospital care than patients without symptoms.</p>
   <p>While some studies have examined healthcare costs for MDD patients in China, there is a paucity of research on the cost and cost-effectiveness of treating MDD with specific pharmacological interventions. This study was conducted to estimate the cost-effectiveness between a well-established SSRI (fluvoxamine) <xref ref-type="bibr" rid="scirp.137575-12">
     [12]
    </xref> and a new serotonin-norepinephrine reuptake inhibitor (SNRI: desvenlafaxine) in Chinese patients with MDD.</p>
  </sec><sec id="s2">
   <title>2. Methods</title>
   <p>A simple decision tree model comparing two antidepressants for cost effectiveness of treating Chinese patients with major depressive disorder (MDD) for 6 months maintenance period was developed (<xref ref-type="fig" rid="fig1">
     Figure 1
    </xref>).</p>
   <p>This model encompasses pharmacotherapy for the treatment of major depressive disorder (MDD) and the occurrence of relapse events based on the type of medication. In the initial stage of the model, pathways are divided according to the choice of fluvoxamine or desvenlafaxine, for Chinese patients with major depressive disorder.</p>
   <fig id="fig1" position="float">
    <label>Figure 1</label>
    <caption>
     <title>Figure 1. Decision tree model.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/8206699-rId14.jpeg?20241122030518" />
   </fig>
   <p>After the pathways are divided according to each medication, the model progresses based on the occurrence of relapse events. The relapse rates vary depending on the medication, and the relative effectiveness on relapse rates was obtained from a recent network meta-analysis by Kishi et al. (2023). Kishi et al. <xref ref-type="bibr" rid="scirp.137575-3">
     [3]
    </xref> showed risk ratio of relapse during the maintenance phase as 0.298 (95% CI = [0.114, 0.686]) and 0.527 (95% CI = [0.347, 0.787]), for fluvoxamine and desvenlafaxine, respectively. Local drug cost was collected from various sources and defined daily dose (DDD) from WHO ATC/DDD index (ATC = N06A antidepressants) was used to estimate the median antidepressant cost for the 180-day maintenance phase: fluvoxamine for 1080 CNY versus desvenlafaxine for 5008 CNY. Since the local cost for relapse could not be found, the following method was applied to estimate the relapse cost in China. Using the relapse costs reported by Gauthier et al. <xref ref-type="bibr" rid="scirp.137575-13">
     [13]
    </xref>, we determined that 2015 USD 7037 per patient per year (PPPY) out of 2015 USD 14416.84 translates to 24.4% of the annual treatment cost of depression for six months. Additionally, Hu et al. <xref ref-type="bibr" rid="scirp.137575-10">
     [10]
    </xref> estimated the annual treatment cost of depression per patient in China to be 2957 CNY in 2006 (equivalent to 360 USD in 2006). Due to the unavailability of the Chinese Medical Consumer Price Index (MCPI) from 2006 to 2015, we used the U.S. Medical CPI data to estimate the 2015 annual treatment cost, which resulted in 3929.34 CNY. Consequently, 24.4% of 3929.34 CNY is calculated as 958.98 CNY. Thus, we assumed 1000 CNY as the six-month relapse cost in China and conducted extensive sensitivity analyses. These costs were incorporated into the model to compare the economic impact of each treatment.</p>
   <p>For disutility from a relapse, again there was no local data available, a Swedish study by Sobocki et al. <xref ref-type="bibr" rid="scirp.137575-14">
     [14]
    </xref> was used as follows: Swedish patients with MDD in remission showed a 0.2635 improvement in health related utility measured by EQ-5D instrument. Hence, a utility loss of 0.13 for relapse period during 180-day maintenance phase was assumed.</p>
   <p>The input parameters used in the model are summarized in <xref ref-type="table" rid="table1">
     Table 1
    </xref>.</p>
   <table-wrap id="table1">
    <label>
     <xref ref-type="table" rid="table1">
      Table 1
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.137575-"></xref>Table 1. Input parameters for the model.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td aleft" width="8.83%"><p style="text-align:left">Variable Name</p></td> 
      <td class="custom-bottom-td aleft" width="22.06%"><p style="text-align:left">Variable Description</p></td> 
      <td class="custom-bottom-td aleft" width="14.71%"><p style="text-align:left">Parameter values (costs in CNY)</p></td> 
      <td class="custom-bottom-td aleft" width="24.99%"><p style="text-align:left">Probabilistic Distribution Used</p><p style="text-align:left">[Univariate Sensitivity range]</p></td> 
      <td class="custom-bottom-td aleft" width="29.41%"><p style="text-align:left">Source</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td aleft" width="8.83%"><p style="text-align:left">Relapse_rr</p></td> 
      <td class="custom-top-td aleft" width="22.06%"><p style="text-align:left">Underlying risk of Relapse (Placebo)</p></td> 
      <td class="custom-top-td aleft" width="14.71%"><p style="text-align:left">0.4</p></td> 
      <td class="custom-top-td aleft" width="24.99%"><p style="text-align:left">Triangular</p><p style="text-align:left">[0.1, 0.7]</p></td> 
      <td class="custom-top-td aleft" width="29.41%"><p style="text-align:left">Assumption</p></td> 
     </tr> 
     <tr> 
      <td class="aleft" width="8.83%"><p style="text-align:left">DES_rr</p></td> 
      <td class="aleft" width="22.06%"><p style="text-align:left">Risk Ratio of Desvenlafaxine compared to Placebo</p></td> 
      <td class="aleft" width="14.71%"><p style="text-align:left">0.527</p></td> 
      <td class="aleft" width="24.99%"><p style="text-align:left">Triangular</p><p style="text-align:left">[0.347, 0.787]</p></td> 
      <td class="aleft" width="29.41%"><p style="text-align:left">Kishi et al. (2023)</p></td> 
     </tr> 
     <tr> 
      <td class="aleft" width="8.83%"><p style="text-align:left">FLV_rr</p></td> 
      <td class="aleft" width="22.06%"><p style="text-align:left">Risk Ratio of Fluvoxamine compared to Placebo</p></td> 
      <td class="aleft" width="14.71%"><p style="text-align:left">0.298</p></td> 
      <td class="aleft" width="24.99%"><p style="text-align:left">Triangular</p><p style="text-align:left">[0.114, 0.686]</p></td> 
      <td class="aleft" width="29.41%"><p style="text-align:left">Kishi et al. (2023)</p></td> 
     </tr> 
     <tr> 
      <td class="aleft" width="8.83%"><p style="text-align:left">DES_c</p></td> 
      <td class="aleft" width="22.06%"><p style="text-align:left">180 day cost of Desvenlafaxine</p></td> 
      <td class="aleft" width="14.71%"><p style="text-align:left">5008</p></td> 
      <td class="aleft" width="24.99%"><p style="text-align:left">Gamma</p><p style="text-align:left">[4006.4, 6009.6]</p></td> 
      <td class="aleft" width="29.41%"><p style="text-align:left">DDD based drug cost</p></td> 
     </tr> 
     <tr> 
      <td class="aleft" width="8.83%"><p style="text-align:left">Util_gain</p></td> 
      <td class="aleft" width="22.06%"><p style="text-align:left">Estimated utility gain for avoiding relapse</p></td> 
      <td class="aleft" width="14.71%"><p style="text-align:left">0.13</p></td> 
      <td class="aleft" width="24.99%"><p style="text-align:left">Triangular</p><p style="text-align:left">[0.104, 0.156]</p></td> 
      <td class="aleft" width="29.41%"><p style="text-align:left">Sobocki et al. (2007)</p></td> 
     </tr> 
     <tr> 
      <td class="aleft" width="8.83%"><p style="text-align:left">FLV_c</p></td> 
      <td class="aleft" width="22.06%"><p style="text-align:left">180 day cost of fluvoxamine</p></td> 
      <td class="aleft" width="14.71%"><p style="text-align:left">1080</p></td> 
      <td class="aleft" width="24.99%"><p style="text-align:left">Gamma</p><p style="text-align:left">[864, 1296]</p></td> 
      <td class="aleft" width="29.41%"><p style="text-align:left">DDD based drug cost</p></td> 
     </tr> 
     <tr> 
      <td class="aleft" width="8.83%"><p style="text-align:left">Relapse_c</p></td> 
      <td class="aleft" width="22.06%"><p style="text-align:left">Cost of treating relapse</p></td> 
      <td class="aleft" width="14.71%"><p style="text-align:left">CNY 1000</p></td> 
      <td class="aleft" width="24.99%"><p style="text-align:left">Gamma</p><p style="text-align:left">[800, 1200]</p></td> 
      <td class="aleft" width="29.41%"><p style="text-align:left">Gauthier et al. (2019) applied to Hu et al. (2007) after inflation adjustment</p></td> 
     </tr> 
    </table>
   </table-wrap>
   <p>In this model, the incremental cost effectiveness ratio (ICER) between fluvoxamine and desvenlafaxine was used to assess the cost-effectiveness during the maintenance phase for Chinese patients with major depressive disorder (MDD). The ICER is defined as the ratio of the difference in costs over effectiveness measured by health related utility between two antidepressant interventions. To judge the cost effectiveness, the estimated ICER is compared to the cost effectiveness threshold value in China, or the value of one additional quality-adjusted life year (QALY) in China. According to Cai et al. <xref ref-type="bibr" rid="scirp.137575-15">
     [15]
    </xref>, the cost effectiveness threshold value in China was estimated as 1.5 times gross domestic product (GDP) which corresponds to CNY 138,332 in 2023.</p>
   <p>Since many assumed input parameters were inevitably used, extensive sensitivity analyses was employed to examine uncertainties from these parameters. A tornado diagram was used to summarize univariate sensitivity analyses. Probabilistic sensitivity analyses with 10,000 simulations using the probabilistic distributions of input parameters and cost effectiveness acceptability curve were used to summarize the results of probabilistic sensitivity analyses.</p>
  </sec><sec id="s3">
   <title>3. Results</title>
   <p>Fluvoxamine was found to be dominating over desvenlafaxine, with cost savings of 4003 CNY and 0.0098 QALY higher over 180-day maintenance phase. The analysis demonstrated that fluvoxamine dominates desvenlafaxine in terms of both costs and effectiveness in China, indicating a strong economic advantage in China.</p>
   <p>Univariate sensitivity analyses were presented by a Tornado diagram in <xref ref-type="fig" rid="fig2">
     Figure 2
    </xref>.</p>
   <fig id="fig2" position="float">
    <label>Figure 2</label>
    <caption>
     <title>Figure 2. Tornado diagram.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/8206699-rId15.jpeg?20241122030518" />
   </fig>
   <p>The most sensitive parameters in the univariate sensitivity analyses were the relapse rates, followed by the cost of desvenlafaxine and the utility loss due to relapse. However, the default result of the dominance of fluvoxamine over desvenlafaxine was not changed by any univariate sensitivity analysis.</p>
   <p>Extensive probabilistic sensitivity analyses based on 10,000 simulations were performed and the results are shown in <xref ref-type="fig" rid="fig3">
     Figure 3
    </xref>.</p>
   <fig id="fig3" position="float">
    <label>Figure 3</label>
    <caption>
     <title>Figure 3. Probabilistic sensitivity analysis.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/8206699-rId16.jpeg?20241122030518" />
   </fig>
   <p>Probabilistic sensitivity analyses demonstrated almost certain results, the probability of being more cost-effective than the comparator was 99.93% for fluvoxamine at 1.5 times the GDP cost effectiveness threshold.</p>
  </sec><sec id="s4">
   <title>4. Concluding Remarks</title>
   <p>This study evaluated the cost-effectiveness of fluvoxamine compared to desvenlafaxine for treating Chinese patients with major depressive disorder (MDD) over a six-month maintenance period. The analysis demonstrated that fluvoxamine is more cost-effective than desvenlafaxine, with a particularly strong cost-effectiveness profile and low uncertainty during this period. These findings highlight fluvoxamine as a viable treatment option for MDD due to its economic advantages. However, the study’s reliance on assumptions and the lack of localized cost data are limitations, suggesting that future research should incorporate more specific regional data. Also disutilities from side effects were not included in the analysis because of lack of local data. Kishi et al. <xref ref-type="bibr" rid="scirp.137575-3">
     [3]
    </xref> reported desvenlafaxine showed significantly higher risk ratio of nausea/vomiting during the maintenance phase than fluvoxamine (RR = 3.011 vs 0.840) in their network meta-analysis. Overall, fluvoxamine offers a cost-effective alternative for managing MDD, especially when balancing treatment outcomes with economic considerations.</p>
  </sec>
 </body><back>
  <ref-list>
   <title>References</title>
   <ref id="scirp.137575-ref1">
    <label>1</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. American Psychiatric Association.
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref2">
    <label>2</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     WHO (2017) Depression and Other Common Mental Disorders: Global Health Estimates. World Health Organization.
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref3">
    <label>3</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Kishi, T., Ikuta, T., Sakuma, K., Okuya, M., Hatano, M., Matsuda, Y., et al. (2022) Antidepressants for the Treatment of Adults with Major Depressive Disorder in the Maintenance Phase: A Systematic Review and Network Meta-Analysis. Molecular Psychiatry, 28, 402-409. &gt;https://doi.org/10.1038/s41380-022-01824-z
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref4">
    <label>4</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Milev, R.V., Giacobbe, P., Kennedy, S.H., Blumberger, D.M., Daskalakis, Z.J., Downar, J., et al. (2016) Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder: Section 4. Neurostimulation Treatments. The Canadian Journal of Psychiatry, 61, 561-575. &gt;https://doi.org/10.1177/0706743716660033
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref5">
    <label>5</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Florea, I., Danchenko, N., Brignone, M., Loft, H., Rive, B. and Abetz-Webb, L. (2015) The Effect of Vortioxetine on Health-Related Quality of Life in Patients with Major Depressive Disorder. Clinical Therapeutics, 37, 2309-2323.e6. &gt;https://doi.org/10.1016/j.clinthera.2015.08.008
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref6">
    <label>6</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Gu, L., Xie, J., Long, J., Chen, Q., Chen, Q., Pan, R., et al. (2013) Epidemiology of Major Depressive Disorder in Chinese Mainland: A Systematic Review. PLOS ONE, 8, e65356. &gt;https://doi.org/10.1371/journal.pone.0065356
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref7">
    <label>7</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Zhao, Y., Jin, Y., Rao, W., Zhang, Q., Zhang, L., Jackson, T., et al. (2021) Prevalence of Major Depressive Disorder among Adults in China: A Systematic Review and Meta-analysis. Frontiers in Psychiatry, 12, Article 659470. &gt;https://doi.org/10.3389/fpsyt.2021.659470
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref8">
    <label>8</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Smith, K. (2014) Mental Health: A World of Depression. Nature, 515, 180-181. &gt;https://doi.org/10.1038/515180a
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref9">
    <label>9</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Hou, Z., Jiang, W., Yin, Y., Zhang, Z. and Yuan, Y. (2016) The Current Situation on Major Depressive Disorder in China: Research on Mechanisms and Clinical Practice. Neuroscience Bulletin, 32, 389-397. &gt;https://doi.org/10.1007/s12264-016-0037-6
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref10">
    <label>10</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Hu, T., He, Y., Zhang, M. and Chen, N. (2007) Economic Costs of Depression in China. Social Psychiatry and Psychiatric Epidemiology, 42, 110-116. &gt;https://doi.org/10.1007/s00127-006-0151-2
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref11">
    <label>11</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Hsieh, C. and Qin, X. (2017) Depression Hurts, Depression Costs: The Medical Spending Attributable to Depression and Depressive Symptoms in China. Health Economics, 27, 525-544. &gt;https://doi.org/10.1002/hec.3604
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref12">
    <label>12</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Smulevich, A.B., Ilyina, N.A. and Chitlova, V.V. (2015) Fluvoxamine in Treatment of Depression in Russian Patients: An Open-Label, Uncontrolled and Non-Randomized Multicenter Observational Study. Open Journal of Psychiatry, 5, 320-329. &gt;https://doi.org/10.4236/ojpsych.2015.54036
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref13">
    <label>13</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Gauthier, G., Mucha, L., Shi, S. and Guerin, A. (2019) Economic Burden of Relapse/Recurrence in Patients with Major Depressive Disorder. Journal of Drug Assessment, 8, 97-103. &gt;https://doi.org/10.1080/21556660.2019.1612410
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref14">
    <label>14</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Sobocki, P., Ekman, M., Ågren, H., Krakau, I., Runeson, B., Mårtensson, B., et al. (2007) Health-Related Quality of Life Measured with EQ-5D in Patients Treated for Depression in Primary Care. Value in Health, 10, 153-160. &gt;https://doi.org/10.1111/j.1524-4733.2006.00162.x
    </mixed-citation>
   </ref>
   <ref id="scirp.137575-ref15">
    <label>15</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Cai, D., Shi, S., Jiang, S., Si, L., Wu, J. and Jiang, Y. (2021) Estimation of the Cost-Effective Threshold of a Quality-Adjusted Life Year in China Based on the Value of Statistical Life. The European Journal of Health Economics, 23, 607-615. &gt;https://doi.org/10.1007/s10198-021-01384-z
    </mixed-citation>
   </ref>
  </ref-list>
 </back>
</article>