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<article article-type="research-article" dtd-version="1.1" specific-use="sps-1.9" xml:lang="en" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">
	<front>
		<journal-meta>
			<journal-id journal-id-type="publisher-id">abcimg</journal-id>
			<journal-title-group>
				<journal-title>ABC Imagem Cardiovascular</journal-title>
				<abbrev-journal-title abbrev-type="publisher">Arq Bras Cardiol: Imagem cardiovasc.</abbrev-journal-title>
			</journal-title-group>
			<issn pub-type="epub">2675-312X</issn>
			<publisher>
				<publisher-name>Sociedade Brasileira de Cardiologia</publisher-name>
			</publisher>
		</journal-meta>
		<article-meta>
			<article-id pub-id-type="doi">10.36660/abcimg.20240108i</article-id>
			<article-id pub-id-type="publisher-id">abcimg.20240108i</article-id>
			<article-categories>
				<subj-group subj-group-type="heading">
					<subject>Original Article</subject>
				</subj-group>
			</article-categories>
			<title-group>
				<article-title>Variations in Myocardial FDG Uptake and Metformin Use: Implications for Survival during Immunotherapy</article-title>
			</title-group>
			<contrib-group>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0002-0761-9856</contrib-id>
					<name>
						<surname>Torres</surname>
						<given-names>Matheus Coelho</given-names>
					</name>
					<role>Conception and design of the research</role>
					<role>acquisition of data</role>
					<role>analysis and interpretation of the data and writing of the manuscript</role>
					<role>statistical analysis</role>
					<role>critical revision of the manuscript for intellectual content</role>
					<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
					<xref ref-type="corresp" rid="c1"/>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0002-6983-6506</contrib-id>
					<name>
						<surname>Fagundes</surname>
						<given-names>Juliana Goes Martins</given-names>
					</name>
					<role>Conception and design of the research</role>
					<role>acquisition of data</role>
					<role>analysis and interpretation of the data and writing of the manuscript</role>
					<role>critical revision of the manuscript for intellectual content</role>
					<role>obtaining financing</role>
					<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0001-6737-1760</contrib-id>
					<name>
						<surname>Botelho</surname>
						<given-names>Luís Fábio Barbosa</given-names>
					</name>
					<role>analysis and interpretation of the data and writing of the manuscript</role>
					<role>critical revision of the manuscript for intellectual content</role>
					<role>statistical analysis</role>
					<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0009-0007-9626-0630</contrib-id>
					<name>
						<surname>Verçosa</surname>
						<given-names>Alinne Fernanda Amaral</given-names>
					</name>
					<role>acquisition of data</role>
					<role>analysis and interpretation of the data and writing of the manuscript</role>
					<role>critical revision of the manuscript for intellectual content</role>
					<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0001-8809-8783</contrib-id>
					<name>
						<surname>Melo</surname>
						<given-names>Marcelo Dantas Tavares de</given-names>
					</name>
					<role>Conception and design of the research</role>
					<role>acquisition of data</role>
					<role>analysis and interpretation of the data and writing of the manuscript</role>
					<role>statistical analysis</role>
					<role>critical revision of the manuscript for intellectual content</role>
					<role>obtaining financing</role>
					<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
				</contrib>
				<aff id="aff1">
					<label>1</label>
					<institution content-type="orgname">Universidade Federal da Paraíba</institution>
					<addr-line>
						<named-content content-type="city">João Pessoa</named-content>
						<named-content content-type="state">PB</named-content>
					</addr-line>
					<country country="BR">Brazil</country>
					<institution content-type="original">Universidade Federal da Paraíba, João Pessoa, PB – Brazil</institution>
				</aff>
				<aff id="aff2">
					<label>2</label>
					<institution content-type="orgname">Grupo Oncoclínicas</institution>
					<addr-line>
						<named-content content-type="city">João Pessoa</named-content>
						<named-content content-type="state">PB</named-content>
					</addr-line>
					<country country="BR">Brazil</country>
					<institution content-type="original">Grupo Oncoclínicas, João Pessoa, PB – Brazil</institution>
				</aff>
				<aff id="aff3">
					<label>3</label>
					<institution content-type="orgname">Nova Diagnóstico por Imagem</institution>
					<addr-line>
						<named-content content-type="city">João Pessoa</named-content>
						<named-content content-type="state">PB</named-content>
					</addr-line>
					<country country="BR">Brazil</country>
					<institution content-type="original">Nova Diagnóstico por Imagem, João Pessoa, PB – Brazil</institution>
				</aff>
			</contrib-group>
			<author-notes>
				<corresp id="c1">
					<label>Mailing Address:</label><bold>Matheus Coelho Torres</bold> • Universidade Federal da Paraíba. Bacharel José de Oliveira Curchatuz, 15. Postal code: 58036-130. João Pessoa, PB – Brazil E-mail: <email>matheuscoelhotorres@gmail.com</email>
				</corresp>
				<fn fn-type="conflict">
					<label>Potential Conflict of Interest</label>
					<p>No potential conflict of interest relevant to this article was reported.</p>
				</fn>
				<fn fn-type="edited-by">
					<label>Editor responsible for the review:</label>
					<p>Marcelo Tavares</p>
				</fn>
			</author-notes>
			<pub-date date-type="pub" publication-format="electronic">
				<day>30</day>
				<month>01</month>
				<year>2025</year>
			</pub-date>
			<pub-date date-type="collection" publication-format="electronic">
				<year>2025</year>
			</pub-date>
			<volume>38</volume>
			<issue>1</issue>
			<elocation-id>e20240108</elocation-id>
			<history>
				<date date-type="received">
					<day>26</day>
					<month>10</month>
					<year>2024</year>
				</date>
				<date date-type="rev-recd">
					<day>28</day>
					<month>10</month>
					<year>2024</year>
				</date>
				<date date-type="accepted">
					<day>28</day>
					<month>10</month>
					<year>2024</year>
				</date>
			</history>
			<permissions>
				<license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/" xml:lang="en">
					<license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License</license-p>
				</license>
			</permissions>
			<abstract>
				<title>Abstract</title>
				<sec>
					<title>Background:</title>
					<p>The rise of immune checkpoint inhibitors (ICIs) has significantly improved lung cancer outcomes; however, there is a lack of response prediction protocols. Furthermore, preclinical studies have indicated a promising association between metformin, β-blockers (BBs), and improved cancer patient outcomes.</p>
				</sec>
				<sec>
					<title>Objectives:</title>
					<p>The primary objective of this study was to investigate metformin's impact on survival outcomes. The secondary objectives included assessing myocardial FDG uptake variation (change in standardized uptake value [ΔSUV]) during ICI treatment and evaluating the effects of smoking, diabetes, hypertension, and BB usage on survival outcomes.</p>
				</sec>
				<sec>
					<title>Methods:</title>
					<p>This single-arm, unicentric retrospective cohort study evaluated lung cancer patients who started using ICIs from July 2016 to December 2021. Inclusion criteria were age 18 years or above, lung cancer treated with ICIs (CTLA-4, PD-1, and PD-L1 inhibitors), and having undergone at least two positron emission tomography-computed tomography (PET-CT) scans.</p>
				</sec>
				<sec>
					<title>Results:</title>
					<p>Fifty-eight patients fulfilled all the inclusion criteria. Metformin users presented a 759-day increase in overall survival (OS) (p = 0.015). A trend of a 161-day increase in progression-free survival was observed in patients with positive myocardial ΔSUV compared to the negative ΔSUV group (p = 0.066), along with a trend of a 285-day increase in favor of BB users (p=0.886).</p>
				</sec>
				<sec>
					<title>Conclusion:</title>
					<p>The significant association between metformin use and increased OS suggests metformin as a promising adjuvant for ICI therapy. A trend of positive myocardial ΔSUV and improved outcomes may suggest a potential role of PET-CT in response prediction; however, larger studies are necessary to solidify this hypothesis.</p>
				</sec>
			</abstract>
			<kwd-group xml:lang="en">
				<title>Keywords:</title>
				<kwd>Immune Checkpoint Inhibitors</kwd>
				<kwd>Positron Emission Tomography-Computed Tomography</kwd>
				<kwd>Metformin</kwd>
				<kwd>Cardio-Oncology</kwd>
				<kwd>Cardiotoxicity</kwd>
			</kwd-group>
			<counts>
				<fig-count count="8"/>
				<table-count count="4"/>
				<equation-count count="0"/>
				<ref-count count="34"/>
			</counts>
		</article-meta>
	</front>
	<body>
		<sec sec-type="intro">
			<title>Introduction</title>
			<p>Immune system evasion represents a pivotal mechanism in carcinogenesis, whereby tumor cells employ various mechanisms to elude immune surveillance. These mechanisms encompass the downregulation of tumor antigen presentation and the exposure of molecules that impede directed immune response.<sup><xref ref-type="bibr" rid="B1">1</xref></sup> Notably, lung cancer, the leading cause of global cancer-related deaths, is frequently approached by the utilization of immune checkpoint inhibitors (ICIs) as a treatment modality. These therapeutic agents function by impeding the detrimental regulatory mechanisms enacted by the tumor, thus fostering an enhanced immune defense against malignant growth.</p>
			<p>Despite limited improvements in 5-year survival rates among lung cancer patients, 2-year survival rates have significantly increased.<sup><xref ref-type="bibr" rid="B2">2</xref></sup> This improvement can be largely attributed to the well-documented efficacy of ICI therapy in enhancing long-term overall survival (OS) and progression-free survival (PFS).<sup><xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B4">4</xref></sup> In addition to the stand-alone effectiveness of ICI therapy, the safety and effectiveness of combination regimens involving immunotherapy and chemotherapy,<sup><xref ref-type="bibr" rid="B5">5</xref></sup> platinum-based regimens,<sup><xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B7">7</xref></sup> and/or radiotherapy<sup><xref ref-type="bibr" rid="B8">8</xref>,<xref ref-type="bibr" rid="B9">9</xref></sup> have been extensively reported.</p>
			<p>However, predicting immunotherapy response and the impact of synergistic drugs on treatment outcomes remains uncertain. Although some evidence supports the safety and efficacy of adjuvant drugs such as β-blockers (BBs),<sup><xref ref-type="bibr" rid="B10">10</xref></sup> metformin,<sup><xref ref-type="bibr" rid="B11">11</xref></sup> and albendazole<sup><xref ref-type="bibr" rid="B12">12</xref></sup> through murine models, retrospective data, and meta-analyses, high-quality clinical trials are still needed.</p>
			<p>As further research is needed to establish the role of these adjuvant drugs, their potential to complement ICI therapy and contribute to improved patient outcomes remains a subject of hypotheses and speculation. Certain positron emission tomography-computed tomography (PET-CT) models have been proposed to predict immunotherapy response by analyzing standardized uptake value variation (ΔSUV) and employing PET tracers targeting ICIs, including PD-L1. Nevertheless, the absence of standardized evidence and ambiguous implications for clinical practice present ongoing challenges.<sup><xref ref-type="bibr" rid="B13">13</xref>–<xref ref-type="bibr" rid="B15">15</xref></sup></p>
			<fig id="f4">
				<graphic xlink:href="2675-312X-abcimg-38-01-e20240108-gf04.tif"/>
			</fig>
			<p>Thus, we propose to evaluate the role of adjuvant drugs, such as metformin, on ICI therapy prognosis and to assess changes in myocardial FDG uptake (MGU) rate in advanced lung cancer patients undergoing ICI treatment. Our investigation aims to explore MGU's potential as a monitoring tool for immunotherapy response and the effects of metformin, BBs, and other drugs on survival in immunotherapy.</p>
		</sec>
		<sec sec-type="methods">
			<title>Methods</title>
			<sec>
				<title>Study design and participants</title>
				<p>This retrospective cohort study is a single-arm, unicentric investigation that utilized electronic medical records and PET-CT images to evaluate lung cancer patients who initiated ICI treatment between July 2016 and December 2021. Inclusion criteria included age 18 or above, lung cancer treated with ICIs (Cytotoxic T-lymphocyte associated protein 4 - CTLA-4, Programmed Death 1 PD-1, and Programmed-Death Ligand 1 PD-L1 inhibitors), and having undergone at least two PET-CT scans – one at baseline and another during the course of treatment.</p>
				<p>The primary objective of the study was to assess the variation in MGU rate, measured by the ΔSUV, during the administration of ICIs and their impact on survival outcomes. The secondary objectives aimed to investigate the potential positive or negative effects associated with smoking, diabetes, hypertension, metformin usage, and BB usage on survival outcomes.</p>
				<p>Ethical approval for this research was obtained from the ethics committee under the registration number CAAE 47402321.9.0000.5186</p>
			</sec>
			<sec>
				<title>Statistical analysis</title>
				<p>Descriptive statistics for numerical variables were presented as median and interquartile range, while categorical variables were described using absolute and relative frequencies. The Mann-Whitney test was employed to compare medians between groups. PFS and OS were estimated using the Kaplan-Meier method, and the log-rank test was utilized to compare survival curves. The significance level (alpha) was set at 0.05.</p>
			</sec>
		</sec>
		<sec sec-type="results">
			<title>Results</title>
			<p>Among the 114 patients with lung cancer who underwent immunotherapy at our medical center, 58 patients met the inclusion criteria. Of these, 25 were female and 33 were male, with a median age of 68 years (standard deviation [SD] ±10). The median body mass index was 26 (SD ±4), and the median interval from baseline PET scan to treatment start was 27 days (SD ±47).</p>
			<p>Nearly 52% of the patients received immunotherapy in combination with chemotherapy, while the remaining 48% received immunotherapy alone. Within our sample, 31 patients (53.45%) exhibited a positive ΔSUV, indicating an increase in MGU. Conversely, 25 patients (43.10%) showed a negative ΔSUV, indicating a decrease in MGU. Two patients (3.45%) had no SUV variation and were excluded from the subgroup analysis. The subgroups with positive and negative ΔSUV were comparable, except for a prolonged interval between baseline PET scan and treatment start in the negative ΔSUV group. Detailed clinical and demographic data are shown in <xref ref-type="table" rid="t1">Table 1</xref>, and <xref ref-type="table" rid="t2">Table 2</xref> shows the histological and treatment characteristics of the study population.</p>
			<table-wrap id="t1">
				<label>Table 1</label>
				<caption>
					<title>Demographic characteristics and subgroup distribution of the study population (n = 58), +δSUV and –δSUV subgroups.</title>
				</caption>
				<table frame="hsides" rules="none">
					<colgroup width="14%">
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
					</colgroup>
					<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
						<tr style="background-color:#C58874">
							<th align="left" valign="middle"/>
							<th align="center" colspan="2" valign="middle">Global study population</th>
							<th align="center" colspan="2" valign="middle">ΔSUV+</th>
							<th align="center" colspan="2" valign="middle">ΔSUV–</th>
						</tr>
						<tr style="background-color:#C58874">
							<th align="left" valign="middle"/>
							<th align="center" valign="middle">Median</th>
							<th align="center" valign="middle">SD</th>
							<th align="center" colspan="2" valign="middle">Median</th>
							<th align="center" colspan="2" valign="middle">Median</th>
						</tr>
					</thead>
					<tbody style="border-bottom: thin solid; border-color: #000000">
						<tr>
							<td align="left" valign="middle">Age, yrs</td>
							<td align="center" valign="middle">68</td>
							<td align="center" valign="middle">±10</td>
							<td align="center" colspan="2" valign="middle">67.0096</td>
							<td align="center" colspan="2" valign="middle">68.5336</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">BMI, kg/m<sup>2</sup></td>
							<td align="center" valign="middle">26</td>
							<td align="center" valign="middle">±4</td>
							<td align="center" colspan="2" valign="middle">26.01</td>
							<td align="center" colspan="2" valign="middle">26.26</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Interval between baseline PET and treatment start, days</td>
							<td align="center" valign="middle">27</td>
							<td align="center" valign="middle">±47</td>
							<td align="center" colspan="2" valign="middle">31.58</td>
							<td align="center" colspan="2" valign="middle">52.52</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Sex</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Female</td>
							<td align="center" valign="middle">25</td>
							<td align="center" valign="middle">43</td>
							<td align="center" valign="middle">14</td>
							<td align="center" valign="middle">45.16</td>
							<td align="center" valign="middle">10</td>
							<td align="center" valign="middle">40</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Male</td>
							<td align="center" valign="middle">33</td>
							<td align="center" valign="middle">57</td>
							<td align="center" valign="middle">17</td>
							<td align="center" valign="middle">54.84</td>
							<td align="center" valign="middle">15</td>
							<td align="center" valign="middle">60</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Comorbidities</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Hypertension</td>
							<td align="center" valign="middle">28</td>
							<td align="center" valign="middle">48</td>
							<td align="center" valign="middle">14</td>
							<td align="center" valign="middle">45.16</td>
							<td align="center" valign="middle">12</td>
							<td align="center" valign="middle">48</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Diabetes</td>
							<td align="center" valign="middle">12</td>
							<td align="center" valign="middle">21</td>
							<td align="center" valign="middle">5</td>
							<td align="center" valign="middle">16.12</td>
							<td align="center" valign="middle">7</td>
							<td align="center" valign="middle">28</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Tabagism</td>
							<td align="center" valign="middle">43</td>
							<td align="center" valign="middle">74</td>
							<td align="center" valign="middle">21</td>
							<td align="center" valign="middle">67.74</td>
							<td align="center" valign="middle">20</td>
							<td align="center" valign="middle">80</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Coronary disease</td>
							<td align="center" valign="middle">4</td>
							<td align="center" valign="middle">7</td>
							<td align="center" valign="middle">2</td>
							<td align="center" valign="middle">6.45</td>
							<td align="center" valign="middle">2</td>
							<td align="center" valign="middle">8</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Heart failure (HF)</td>
							<td align="center" valign="middle">1</td>
							<td align="center" valign="middle">2</td>
							<td align="center" valign="middle">0</td>
							<td align="center" valign="middle">0</td>
							<td align="center" valign="middle">1</td>
							<td align="center" valign="middle">4</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Drug usage</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">BBs</td>
							<td align="center" valign="middle">14</td>
							<td align="center" valign="middle">24</td>
							<td align="center" valign="middle">7</td>
							<td align="center" valign="middle">22.58</td>
							<td align="center" valign="middle">6</td>
							<td align="center" valign="middle">24</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">ACE/ARB</td>
							<td align="center" valign="middle">17</td>
							<td align="center" valign="middle">29</td>
							<td align="center" valign="middle">9</td>
							<td align="center" valign="middle">29.03</td>
							<td align="center" valign="middle">7</td>
							<td align="center" valign="middle">28</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Metformin</td>
							<td align="center" valign="middle">8</td>
							<td align="center" valign="middle">14</td>
							<td align="center" valign="middle">3</td>
							<td align="center" valign="middle">9.68</td>
							<td align="center" valign="middle">4</td>
							<td align="center" valign="middle">16</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Anticoagulants</td>
							<td align="center" valign="middle">3</td>
							<td align="center" valign="middle">5</td>
							<td align="center" valign="middle">3</td>
							<td align="center" valign="middle">9.68</td>
							<td align="center" valign="middle">0</td>
							<td align="center" valign="middle">0</td>
						</tr>
					</tbody>
				</table>
				<table-wrap-foot>
					<fn id="TFN1">
						<p>SUV: standardized uptake value; SD: standard deviation; BMI: PET: positron emission tomography-computed tomography; HF: Heart failure; BB: β-blockers; ACE/ARB: angiotensin-converting enzyme/Angiotensin II receptor blockers.</p>
					</fn>
				</table-wrap-foot>
			</table-wrap>
			<table-wrap id="t2">
				<label>Table 2</label>
				<caption>
					<title>Histological and treatment characteristics of the study population.</title>
				</caption>
				<table frame="hsides" rules="none">
					<colgroup width="14%">
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
						<col/>
					</colgroup>
					<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
						<tr style="background-color:#C58874">
							<th align="left" valign="middle"/>
							<th align="center" colspan="2" valign="middle">Global study population</th>
							<th align="center" colspan="2" valign="middle">ΔSUV+</th>
							<th align="center" colspan="2" valign="middle">ΔSUV–</th>
						</tr>
					</thead>
					<tbody style="border-bottom: thin solid; border-color: #000000">
						<tr>
							<td align="left" valign="middle">Histology</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Adenocarcinoma</td>
							<td align="center" valign="middle">43</td>
							<td align="center" valign="middle">74</td>
							<td align="center" valign="middle">23</td>
							<td align="center" valign="middle">74.19</td>
							<td align="center" valign="middle">18</td>
							<td align="center" valign="middle">72</td>
						</tr>
						<tr>
							<td align="left" valign="middle">SCC</td>
							<td align="center" valign="middle">4</td>
							<td align="center" valign="middle">7</td>
							<td align="center" valign="middle">2</td>
							<td align="center" valign="middle">6.45</td>
							<td align="center" valign="middle">2</td>
							<td align="center" valign="middle">8</td>
						</tr>
						<tr>
							<td align="left" valign="middle">NSCLC</td>
							<td align="center" valign="middle">5</td>
							<td align="center" valign="middle">9</td>
							<td align="center" valign="middle">2</td>
							<td align="center" valign="middle">6.45</td>
							<td align="center" valign="middle">2</td>
							<td align="center" valign="middle">8</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Others</td>
							<td align="center" valign="middle">6</td>
							<td align="center" valign="middle">10</td>
							<td align="center" valign="middle">4</td>
							<td align="center" valign="middle">12.9</td>
							<td align="center" valign="middle">3</td>
							<td align="center" valign="middle">12</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Immunotherapy</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Atezolizumab</td>
							<td align="center" valign="middle">14</td>
							<td align="center" valign="middle">24</td>
							<td align="center" valign="middle">6</td>
							<td align="center" valign="middle">19.35</td>
							<td align="center" valign="middle">8</td>
							<td align="center" valign="middle">32</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Durvalumab</td>
							<td align="center" valign="middle">5</td>
							<td align="center" valign="middle">9</td>
							<td align="center" valign="middle">3</td>
							<td align="center" valign="middle">9.68</td>
							<td align="center" valign="middle">1</td>
							<td align="center" valign="middle">4</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Nivolumab</td>
							<td align="center" valign="middle">13</td>
							<td align="center" valign="middle">22</td>
							<td align="center" valign="middle">7</td>
							<td align="center" valign="middle">22.58</td>
							<td align="center" valign="middle">6</td>
							<td align="center" valign="middle">24</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Pembrolizumab</td>
							<td align="center" valign="middle">26</td>
							<td align="center" valign="middle">45</td>
							<td align="center" valign="middle">15</td>
							<td align="center" valign="middle">48.38</td>
							<td align="center" valign="middle">10</td>
							<td align="center" valign="middle">40</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Treatment type</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
						</tr>
						<tr>
							<td align="left" valign="middle">QT-IO</td>
							<td align="center" valign="middle">30</td>
							<td align="center" valign="middle">52</td>
							<td align="center" valign="middle">17</td>
							<td align="center" valign="middle">54.84</td>
							<td align="center" valign="middle">12</td>
							<td align="center" valign="middle">48</td>
						</tr>
						<tr>
							<td align="left" valign="middle">IO</td>
							<td align="center" valign="middle">28</td>
							<td align="center" valign="middle">48</td>
							<td align="center" valign="middle">14</td>
							<td align="center" valign="middle">45.16</td>
							<td align="center" valign="middle">13</td>
							<td align="center" valign="middle">52</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Treatment line</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">1st line</td>
							<td align="center" valign="middle">35</td>
							<td align="center" valign="middle">60</td>
							<td align="center" valign="middle">19</td>
							<td align="center" valign="middle">61.29</td>
							<td align="center" valign="middle">14</td>
							<td align="center" valign="middle">56</td>
						</tr>
						<tr style="background-color:#E8CCBF">
							<td align="left" valign="middle">Subsequent lines</td>
							<td align="center" valign="middle">23</td>
							<td align="center" valign="middle">40</td>
							<td align="center" valign="middle">12</td>
							<td align="center" valign="middle">38.71</td>
							<td align="center" valign="middle">11</td>
							<td align="center" valign="middle">44</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Tumor genetic analysis</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
							<td align="center" valign="middle">N</td>
							<td align="center" valign="middle">%</td>
						</tr>
						<tr>
							<td align="left" valign="middle">ALK/EGFR</td>
							<td align="center" valign="middle">9</td>
							<td align="center" valign="middle">15</td>
							<td align="center" valign="middle">4</td>
							<td align="center" valign="middle">12.9</td>
							<td align="center" valign="middle">4</td>
							<td align="center" valign="middle">16</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Without mutation</td>
							<td align="center" valign="middle">23</td>
							<td align="center" valign="middle">40</td>
							<td align="center" valign="middle">14</td>
							<td align="center" valign="middle">45.16</td>
							<td align="center" valign="middle">10</td>
							<td align="center" valign="middle">40</td>
						</tr>
						<tr>
							<td align="left" valign="middle">Unknown</td>
							<td align="center" valign="middle">26</td>
							<td align="center" valign="middle">45</td>
							<td align="center" valign="middle">13</td>
							<td align="center" valign="middle">41.94</td>
							<td align="center" valign="middle">11</td>
							<td align="center" valign="middle">44</td>
						</tr>
						<tr>
							<td align="left" valign="middle">PD-L1: &gt;50%</td>
							<td align="center" valign="middle">8</td>
							<td align="center" valign="middle">14</td>
							<td align="center" valign="middle">3</td>
							<td align="center" valign="middle">9.68</td>
							<td align="center" valign="middle">4</td>
							<td align="center" valign="middle">16</td>
						</tr>
						<tr>
							<td align="left" valign="middle">PD-L1: 1%–50%</td>
							<td align="center" valign="middle">9</td>
							<td align="center" valign="middle">15</td>
							<td align="center" valign="middle">8</td>
							<td align="center" valign="middle">25.81</td>
							<td align="center" valign="middle">1</td>
							<td align="center" valign="middle">4</td>
						</tr>
						<tr>
							<td align="left" valign="middle">PD-L1: &lt;1%</td>
							<td align="center" valign="middle">10</td>
							<td align="center" valign="middle">17</td>
							<td align="center" valign="middle">6</td>
							<td align="center" valign="middle">19.35</td>
							<td align="center" valign="middle">7</td>
							<td align="center" valign="middle">28</td>
						</tr>
						<tr>
							<td align="left" valign="middle">PD-L1: unknown</td>
							<td align="center" valign="middle">31</td>
							<td align="center" valign="middle">53</td>
							<td align="center" valign="middle">14</td>
							<td align="center" valign="middle">45.16</td>
							<td align="center" valign="middle">13</td>
							<td align="center" valign="middle">52</td>
						</tr>
					</tbody>
				</table>
				<table-wrap-foot>
					<fn id="TFN2">
						<p>SUV: standardized uptake value; SCC: squamous cell carcinoma; NSCLC: Non-small cell lung cancer; QT-IO: Chemotherapy in combination with Immunotherapy; ALK/EGFR: Anaplastic Lymphoma Kinase (ALK) or Epidermal Growth Factor Receptor (EGFR) mutations.</p>
					</fn>
				</table-wrap-foot>
			</table-wrap>
			<p>Among the documented comorbidities, the highest prevalence was observed for tabagism (74%), followed by hypertension (48%) and diabetes (21%). The most commonly used drugs were angiotensin-converting enzyme (ACE) inhibitors or Angiotensin II receptor blockers (ARBs) (29%), BBs (24%), and metformin (14%).</p>
			<p>Regarding the primary outcome, the overall median ΔSUV was +0.05. Within the disease control group, the median ΔSUV was +0.48, indicating an increase in MGU. In contrast, the disease progression group exhibited a median ΔSUV of −0.66.</p>
			<p>When comparing patients with a positive myocardial ΔSUV to those with a negative ΔSUV, there was a median prolongation of PFS by 161 days in favor of the positive myocardial ΔSUV group (p = 0.066). Additionally, an increase of 281 days in OS was observed in the positive myocardial ΔSUV group (p = 0.256) (<xref ref-type="fig" rid="f1">Figure 1</xref>).</p>
			<fig id="f1">
				<label>Figure 1</label>
				<caption>
					<title>ICI: immune checkpoint inhibitors; PET-CT: positron emission tomography-computed tomography; BBs: β-blockers; PFS: progression-free survival; SUV: standardized uptake value; OS: Overall Survival.</title>
				</caption>
				<graphic xlink:href="2675-312X-abcimg-38-01-e20240108-gf01.tif"/>
			</fig>
			<p>Furthermore, diabetic patients demonstrated a noteworthy increase of 759 days in OS (p = 0.023). In subgroup analysis, a trend toward even more favorable outcomes was observed in metformin users (p = 0.015) (<xref ref-type="fig" rid="f2">Figure 2</xref>). Additionally, a non-statistically significant trend of prolongation in OS by 285 days was noticed among BB users (p = 0.886) (<xref ref-type="fig" rid="f3">Figure 3</xref>).</p>
			<fig id="f2">
				<label>Figure 2</label>
				<caption>
					<title>Overall survival comparison between metformin users and non-metformin users.</title>
				</caption>
				<graphic xlink:href="2675-312X-abcimg-38-01-e20240108-gf02.tif"/>
			</fig>
			<fig id="f3">
				<label>Figure 3</label>
				<caption>
					<title>Overall survival comparison between β-blocker users and non-β-blocker users.</title>
				</caption>
				<graphic xlink:href="2675-312X-abcimg-38-01-e20240108-gf03.tif"/>
			</fig>
			<p>However, no statistically significant associations were found between the usage of ACE inhibitors or ARBs, tobacco use, or hypertension and OS or PFS.</p>
		</sec>
		<sec sec-type="discussion">
			<title>Discussion</title>
			<p>The well-documented ability of Fluorodeoxyglucose F 18 (18F-FDG) PET-CT to identify tissue inflammation—a hallmark of immune-related adverse events (irAEs)—indicates its potential for the early detection of subclinical irAEs. Moreover, PET-CT may play a crucial role in confirming suspected irAEs, including myocarditis, by revealing heterogeneous and moderate-to-high increases in 18F-FDG uptake within the left ventricle (LV).<sup><xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref></sup></p>
			<p>The disparity observed in the average cardiac ΔSUV between the disease control group and the disease progression group within our study suggests a potential association between increased SUV following treatment and improved responses to immunotherapy. This finding is further substantiated by the median prolongation of 161 days in PFS (p = 0.066) and 281 days in OS (p = 0.256) among patients exhibiting a positive ΔSUV. These results highlight the potential utility of ΔSUV as a predictive marker for treatment response and prognosis in patients undergoing immunotherapy.</p>
			<p>Although the precise mechanism underlying irAEs is not yet fully understood, it is known that ICIs enhance the immune response against tumors, leading to inflammatory side effects through the recognition of shared antigens between tumor cells and normal tissues. Thus, it is hypothesized that the increase in 18F-FDG uptake, known in inflammatory processes, along with the presence of irAEs, could estimate response to immunotherapy and be associated with positive clinical outcomes.</p>
			<p>Our findings align with a recent systematic review and meta-analysis, which demonstrated a correlation between irAEs and improved OS, PFS, and objective response rates (ORRs) in ICI-treated patients. The increase in SUV was identified as the main irAE marker on PET-CT.<sup><xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B19">19</xref></sup> Similarly, it was found that patients who experienced low- to mid-grade irAEs during atezolizumab-containing treatment regimens exhibited longer OS compared to those with high-grade irAEs or no irAEs at all.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> These findings further support the notion that the occurrence of irAEs, along with changes in MGU, can serve as a valuable prognostic indicator and predictor of treatment response in patients undergoing immunotherapy.</p>
			<p>A significant correlation was observed between increased OS and the usage of metformin (p = 0.015). The relationship between metformin and cancer immunity has been postulated to involve various mechanisms. These include the activation of adenosine monophosphate-activated protein kinase (AMPK)-dependent and AMPK-independent signaling pathways, which exert anti-tumor effects, and the elevation of the exhaustion threshold of cytotoxic T-lymphocytes (CTLs), thereby enhancing immune surveillance. Furthermore, metformin has been shown to impede the immune-inhibitory signaling of PD-L1 through the phosphorylation of PD-L1 associated with AMPK-dependent signaling activation,<sup><xref ref-type="bibr" rid="B21">21</xref></sup> as well as the glycosylation and degradation of PD-L1 within the endoplasmic reticulum.<sup><xref ref-type="bibr" rid="B22">22</xref></sup> These findings support the potential role of metformin as a modulator of cancer immunity and suggest its potential benefits in improving patient outcomes, particularly in terms of OS.</p>
			<p>Consistent with our findings, several studies have demonstrated enhanced treatment outcomes when ICIs are combined with metformin in preclinical models of metastatic melanoma,<sup><xref ref-type="bibr" rid="B23">23</xref></sup> non-small cell lung cancer (NSCLC),<sup><xref ref-type="bibr" rid="B24">24</xref></sup> and breast cancer.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> These studies provide further evidence supporting the potential synergistic effects of combining ICIs with metformin, leading to improved therapeutic responses in various cancer types.</p>
			<p>Furthermore, the combination of metformin with PD-1 blockade has shown promising results in enhancing tumor clearance and improving T-cell function by mitigating tumor-induced hypoxia, which acts as an inhibitory factor for T-cell activity.<sup><xref ref-type="bibr" rid="B25">25</xref></sup> Moreover, in murine models, the synergistic effect of metformin and vaccine immunotherapy has been demonstrated to reduce PD-L1 expression on tumor cells.<sup><xref ref-type="bibr" rid="B11">11</xref></sup> These findings highlight the potential of metformin in modulating the tumor microenvironment, alleviating hypoxia-associated immune suppression, and augmenting the efficacy of immunotherapeutic approaches.</p>
			<p>In the same manner, investigations have examined the potential of combining metformin with anti-PD-1 monotherapy or a combination of anti-VEGFR2 and anti-PD-1 to restore sensitivity to immunotherapies in Nonalcoholic Steatohepatitis-Hepatocellular Carcinoma (NASH-HCC) tumors, which are typically characterized by limited responsiveness. Notably, these studies conducted in mice demonstrated the enhanced therapeutic efficacy achieved through such combinations, providing further support for exploring the synergistic effects of metformin and immunotherapies in overcoming resistance and improving treatment outcomes in challenging tumor types.<sup><xref ref-type="bibr" rid="B26">26</xref>,<xref ref-type="bibr" rid="B27">27</xref></sup></p>
			<p>Although limited in number, the available studies investigating the combination of metformin and ICIs in human subjects have yielded promising results. In an Italian study involving 40 patients, the concomitant administration of metformin and nivolumab was well tolerated and deemed safe. Notably, higher metformin doses (&gt;1,000 mg daily) were associated with longer OS (p = 0.037) and PFS (p = 0.021) and improved response rates, corroborating our own findings.<sup><xref ref-type="bibr" rid="B28">28</xref></sup> Similarly, the combination of metformin with ICIs demonstrated potentially favorable clinical outcomes, although statistical significance was not reached, likely due to the small sample size.<sup><xref ref-type="bibr" rid="B23">23</xref></sup> Furthermore, metformin has been shown to enhance natural killer cell functions in head-and-neck squamous cell carcinoma.<sup><xref ref-type="bibr" rid="B29">29</xref></sup> These preliminary findings suggest that the combination of metformin with ICIs holds promise as a therapeutic strategy, warranting further investigation in larger clinical studies to establish its efficacy and safety profile on humans.</p>
			<p>Hence, based on the multitude of pathways and immunologic mechanisms proposed in preclinical studies and its favorable results, it can be reasonably concluded that metformin may play a significant role as a safe, well-tolerated, and readily available adjuvant therapy in the management of solid cancers when used in conjunction with ICIs.</p>
			<p>The potential role of beta-blockers (BBs) in cancer treatment has been widely investigated, with conflicting evidence found in the literature. Some older retrospective studies have demonstrated improved treatment outcomes in patients with breast cancer, especially in triple-negative,<sup><xref ref-type="bibr" rid="B30">30</xref>,<xref ref-type="bibr" rid="B31">31</xref></sup> ovarian,<sup><xref ref-type="bibr" rid="B32">32</xref></sup> bladder,<sup><xref ref-type="bibr" rid="B33">33</xref></sup> and NSCLCs.<sup><xref ref-type="bibr" rid="B34">34</xref></sup></p>
			<p>Moreover, a possible mechanism of action for BBs in cancer has been proposed in the literature, where beta-adrenergic signaling was found to be related to reduced proliferation of CD8+ T-cells and immune suppression mediated by regulatory T-cells and myeloid-derived suppressor cells.<sup><xref ref-type="bibr" rid="B10">10</xref></sup></p>
			<p>While the observed data regarding BB usage and OS did not reach statistical significance, potentially due to the limited sample size, the trend toward a 285-day increase in OS suggests a possible role for BBs as adjuvant therapy to ICIs in cancer treatment. Further studies with larger sample sizes are warranted to elucidate the underlying mechanism of action and determine whether BBs should be considered as a complementary drug for all patients undergoing immune checkpoint blockade.</p>
			<p>Despite conflicting evidence in the literature regarding the impact of BBs on OS, PFS, and ORRs, similar findings to ours were reported in a recent meta-analysis that included 10,156 patients. The meta-analysis revealed that BB usage was associated with better ORRs to ICIs (odds ratio [OR] = 0.42 [0.19−0.94], p = 0.036), particularly in the subgroup of lung cancer patients (OR = 0.25 [0.08−0.83], p = 0.024). However, no significant association was found between BBs and OS or PFS in the pooled analysis.<sup><xref ref-type="bibr" rid="B29">29</xref></sup></p>
			<p>In summary, while the literature on the relationship between BBs and cancer treatment outcomes remains inconclusive, our findings, along with the meta-analysis results, suggest that BBs may have a potential role as adjunctive therapy to ICIs in cancer treatment that should be further studied.</p>
			<sec>
				<title>Study limitations</title>
				<p>The study has certain limitations that need to be acknowledged. First, the sample size was relatively small, primarily due to the limited number of lung cancer patients who received ICI therapy at our center. Consequently, the statistical significance of some findings may be compromised. Further research involving larger cohorts is essential to strengthen the validity and generalizability of our results.</p>
				<p>Moreover, additional investigations are required to establish the underlying mechanisms of action and determine the clinical significance of using BBs in combination with ICIs. Furthermore, the importance of ΔSUV on survival outcomes also needs to be explored in future studies. These aspects will provide a more comprehensive understanding of the therapeutic potential and prognostic implications associated with the combined use of metformin, BBs, and ICIs in the context of lung cancer treatment.</p>
			</sec>
		</sec>
		<sec sec-type="conclusions">
			<title>Conclusions</title>
			<p>Although further studies are needed to comprehensively assess the relationship between increased MGU and improved outcomes in patients undergoing ICI therapy, the role of PET-CT as a valuable tool for evaluating treatment response and irAEs is well established. Our findings highlight a significant association between increased OS and metformin use. This suggests that metformin could serve as an important adjuvant treatment option for patients undergoing ICI therapy, regardless of their diabetic or hyperglycemic status. Metformin's synergistic effects through multiple pathways, coupled with its accessibility, minimal side effects, and favorable safety profile, underscore its potential in enhancing treatment outcomes.</p>
		</sec>
	</body>
	<back>
		<fn-group>
			<fn fn-type="financial-disclosure" id="fn1">
				<label>Sources of Funding</label>
				<p>There were no external funding sources for this study.</p>
			</fn>
			<fn fn-type="other" id="fn2">
				<label>Study Association</label>
				<p>This study is not associated with any thesis or dissertation work.</p>
			</fn>
			<fn fn-type="other" id="fn3">
				<label>Ethics Approval and Consent to Participate</label>
				<p>This study was approved by the Ethics Committee of the Secretaria de Saúde do Estado da Paraíba – SES/PB under the protocol number 47402321.9.0000.5186. All the procedures in this study were in accordance with the 1975 Helsinki Declaration, updated in 2013. Informed consent was obtained from all participants included in the study.</p>
			</fn>
		</fn-group>
		<ref-list>
			<title>References</title>
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						</name>
						<name>
							<surname>Kroemer</surname>
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					<source>Oncoimmunology: A Practical Guide for Cancer Immunotherapy</source>
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							<surname>Montgomery</surname>
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							<surname>Smedby</surname>
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							<surname>Fall</surname>
							<given-names>K</given-names>
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					<article-title>Beta-Blocker Use and Urothelial Bladder Cancer Survival: A Swedish Register-Based Cohort Study</article-title>
					<source>Acta Oncol</source>
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	</back>
	<sub-article article-type="translation" id="S1" xml:lang="pt">
		<front-stub>
			<article-id pub-id-type="doi">10.36660/abcimg.20240108</article-id>
			<article-categories>
				<subj-group subj-group-type="heading">
					<subject>Artigo Original</subject>
				</subj-group>
			</article-categories>
			<title-group>
				<article-title>Variações na Captação de FDG Miocárdica e Uso de Metformina: Implicações para a Sobrevida Durante a Imunoterapia</article-title>
			</title-group>
			<contrib-group>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0002-0761-9856</contrib-id>
					<name>
						<surname>Torres</surname>
						<given-names>Matheus Coelho</given-names>
					</name>
					<role>Concepção e desenho da pesquisa</role>
					<role>obtenção de dados</role>
					<role>análise e interpretação dos dados e redação do manuscrito</role>
					<role>análise estatística</role>
					<role>revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
					<xref ref-type="aff" rid="aff4"><sup>1</sup></xref>
					<xref ref-type="corresp" rid="c2"/>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0002-6983-6506</contrib-id>
					<name>
						<surname>Fagundes</surname>
						<given-names>Juliana Goes Martins</given-names>
					</name>
					<role>Concepção e desenho da pesquisa</role>
					<role>obtenção de dados</role>
					<role>análise e interpretação dos dados e redação do manuscrito</role>
					<role>revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
					<role>obtenção de financiamento</role>
					<xref ref-type="aff" rid="aff5"><sup>2</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0001-6737-1760</contrib-id>
					<name>
						<surname>Botelho</surname>
						<given-names>Luís Fábio Barbosa</given-names>
					</name>
					<role>análise e interpretação dos dados e redação do manuscrito</role>
					<role>revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
					<role>análise estatística</role>
					<xref ref-type="aff" rid="aff4"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0009-0007-9626-0630</contrib-id>
					<name>
						<surname>Verçosa</surname>
						<given-names>Alinne Fernanda Amaral</given-names>
					</name>
					<role>obtenção de dados</role>
					<role>análise e interpretação dos dados e redação do manuscrito</role>
					<role>revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
					<xref ref-type="aff" rid="aff6"><sup>3</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0001-8809-8783</contrib-id>
					<name>
						<surname>Melo</surname>
						<given-names>Marcelo Dantas Tavares de</given-names>
					</name>
					<role>Concepção e desenho da pesquisa</role>
					<role>obtenção de dados</role>
					<role>análise e interpretação dos dados e redação do manuscrito</role>
					<role>análise estatística</role>
					<role>revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
					<role>obtenção de financiamento</role>
					<xref ref-type="aff" rid="aff4"><sup>1</sup></xref>
				</contrib>
				<aff id="aff4">
					<label>1</label>
					<addr-line>
						<named-content content-type="city">João Pessoa</named-content>
						<named-content content-type="state">PB</named-content>
					</addr-line>
					<country country="BR">Brasil</country>
					<institution content-type="original">Universidade Federal da Paraíba, João Pessoa, PB – Brasil</institution>
				</aff>
				<aff id="aff5">
					<label>2</label>
					<addr-line>
						<named-content content-type="city">João Pessoa</named-content>
						<named-content content-type="state">PB</named-content>
					</addr-line>
					<country country="BR">Brasil</country>
					<institution content-type="original">Grupo Oncoclínicas, João Pessoa, PB – Brasil</institution>
				</aff>
				<aff id="aff6">
					<label>3</label>
					<addr-line>
						<named-content content-type="city">João Pessoa</named-content>
						<named-content content-type="state">PB</named-content>
					</addr-line>
					<country country="BR">Brasil</country>
					<institution content-type="original">Nova Diagnóstico por Imagem, João Pessoa, PB – Brasil</institution>
				</aff>
			</contrib-group>
			<author-notes>
				<corresp id="c2">
					<label>Correspondência:</label><bold>Matheus Coelho Torres</bold> • Universidade Federal da Paraíba. Bacharel José de Oliveira Curchatuz, 15. CEP: 58036-130. João Pessoa, PB – Brasil E-mail: <email>matheuscoelhotorres@gmail.com</email>
				</corresp>
				<fn fn-type="conflict">
					<label>Potencial Conflito de Interesse</label>
					<p>Declaro não haver conflito de interesses pertinentes.</p>
				</fn>
				<fn fn-type="edited-by">
					<label>Editor responsável pela revisão:</label>
					<p>Marcelo Tavares</p>
				</fn>
			</author-notes>
			<abstract>
				<title>Resumo</title>
				<sec>
					<title>Introdução:</title>
					<p>O aumento do uso de inibidores de <italic>checkpoint</italic> imunológicos (ICIs) melhorou significativamente os resultados no câncer de pulmão; no entanto, ainda há falta de protocolos para prever a resposta ao tratamento. Além disso, estudos pré-clínicos indicaram uma associação promissora entre metformina, β-bloqueadores (BBs) e melhores resultados em pacientes com câncer.</p>
				</sec>
				<sec>
					<title>Objetivos:</title>
					<p>O objetivo principal deste estudo foi investigar o impacto da metformina nos desfechos de sobrevida. Os objetivos secundários incluíram a avaliação da variação na captação de FDG no miocárdio (alteração no valor de captação padronizado [ΔSUV]) durante o tratamento com ICIs e a avaliação dos efeitos do tabagismo, diabetes, hipertensão e uso de BBs nos desfechos de sobrevida.</p>
				</sec>
				<sec>
					<title>Métodos:</title>
					<p>Este estudo de coorte retrospectivo unicêntrico e de braço único avaliou pacientes com câncer de pulmão que começaram a usar ICIs de julho de 2016 a dezembro de 2021. Os critérios de inclusão foram: idade superior a 18 anos, câncer de pulmão tratado com ICIs (inibidores de CTLA-4, PD-1 e PD-L1) e realização de pelo menos dois exames de tomografia por emissão de pósitrons combinada à tomografia computadorizada (PET-CT).</p>
				</sec>
				<sec>
					<title>Resultados:</title>
					<p>Cinquenta e oito pacientes preencheram todos os critérios de inclusão. Os usuários de metformina apresentaram um aumento de 759 dias na sobrevida global (SG) (p = 0,015). Uma tendência de aumento de 161 dias na sobrevida livre de progressão (SLP) foi observada nos pacientes com ΔSUV miocárdica positiva em comparação ao grupo com ΔSUV negativa (p = 0,066), juntamente com uma tendência de aumento de 285 dias a favor dos usuários de BBs (p=0,886).</p>
				</sec>
				<sec>
					<title>Conclusão:</title>
					<p>A associação significativa entre o uso de metformina e aumento da SG sugere que a metformina é um adjuvante promissor para a terapia com ICI. Uma tendência de ΔSUV miocárdica positiva e melhores resultados pode sugerir um papel potencial da PET-CT na previsão de resposta, porém, estudos maiores são necessários para solidificar essa hipótese.</p>
				</sec>
			</abstract>
			<kwd-group xml:lang="pt">
				<title>Palavras-chave:</title>
				<kwd>Inibidores de Checkpoint Imunológico</kwd>
				<kwd>Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada</kwd>
				<kwd>Metformina</kwd>
				<kwd>Cardio-Oncologia</kwd>
				<kwd>Cardiotoxicidade</kwd>
			</kwd-group>
		</front-stub>
		<body>
			<fig id="f8">
				<graphic xlink:href="2675-312X-abcimg-38-01-e20240108-gf04-pt.tif"/>
			</fig>
			<sec sec-type="intro">
				<title>Introdução</title>
				<p>A evasão do sistema imunológico constitui um mecanismo crucial na carcinogênese, por meio do qual células tumorais utilizam diversos processos para escapar da vigilância imunológica. Esses processos incluem a regulação negativa da apresentação do antígeno tumoral e a exposição de moléculas que suprimem a resposta imunológica específica.<sup><xref ref-type="bibr" rid="B1">1</xref></sup> Notadamente, o câncer de pulmão, principal causa de mortes relacionadas ao câncer em todo o mundo, é frequentemente tratado com inibidores de <italic>checkpoint</italic> imunológicos (ICIs). Esses agentes terapêuticos atuam bloqueando os mecanismos regulatórios deletérios promovidos pelo tumor, fortalecendo, assim, a defesa imunológica contra o crescimento maligno.</p>
				<p>Apesar das limitadas melhorias nas taxas de sobrevivência em 5 anos entre pacientes com câncer de pulmão, as taxas de sobrevivência em 2 anos apresentaram um aumento significativo.<sup><xref ref-type="bibr" rid="B2">2</xref></sup> Esse avanço pode ser amplamente atribuído à eficácia comprovada da terapia com ICIs em melhorar a sobrevida global (SG) a longo prazo e a sobrevida livre de progressão (SLP).<sup><xref ref-type="bibr" rid="B3">3</xref>,<xref ref-type="bibr" rid="B4">4</xref></sup> Além da eficácia isolada da terapia ICI, a segurança e a efetividade de regimes combinados envolvendo imunoterapia e quimioterapia,<sup><xref ref-type="bibr" rid="B5">5</xref></sup> regimes baseados em platina,<sup><xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B7">7</xref></sup> e/ou radioterapia<sup><xref ref-type="bibr" rid="B8">8</xref>,<xref ref-type="bibr" rid="B9">9</xref></sup> têm sido amplamente documentados.</p>
				<p>No entanto, a previsão da resposta à imunoterapia e o impacto de medicamentos sinérgicos nos resultados do tratamento permanecem incertos. Embora algumas evidências apontem para a segurança e a eficácia de medicamentos adjuvantes, como β-bloqueadores (BBs),<sup><xref ref-type="bibr" rid="B10">10</xref></sup> metformina<sup><xref ref-type="bibr" rid="B11">11</xref></sup> e albendazol,<sup><xref ref-type="bibr" rid="B12">12</xref></sup> com base em modelos murinos, dados retrospectivos e meta-análises, ainda são necessários ensaios clínicos de alta qualidade para confirmar esses achados.</p>
				<p>Embora mais pesquisas sejam necessárias para estabelecer o papel desses medicamentos adjuvantes, seu potencial para complementar a terapia com ICIs e contribuir para melhores desfechos em pacientes permanece no campo das hipóteses e especulações. Modelos específicos de tomografia por emissão de pósitrons combinada à tomografia computadorizada (PET-CT) foram propostos para prever a resposta à imunoterapia, analisando a variação do valor de captação padronizado (ΔSUV) e utilizando traçadores PET direcionados a ICIs, incluindo PD-L1. No entanto, a falta de evidências padronizadas e as implicações ambíguas para a prática clínica continuam a representar desafios significativos.<sup><xref ref-type="bibr" rid="B13">13</xref>–<xref ref-type="bibr" rid="B15">15</xref></sup></p>
				<p>Propõe-se avaliar o papel de medicamentos adjuvantes, como a metformina, no prognóstico da terapia com ICIs, bem como analisar as alterações na taxa de captação de FDG miocárdica (MGU) em pacientes com câncer de pulmão avançado submetidos a esse tratamento. A investigação teve como objetivo explorar o potencial da MGU como ferramenta de monitoramento da resposta à imunoterapia, além de avaliar os efeitos da metformina, dos BBs e outros medicamentos na sobrevivência durante a imunoterapia.</p>
			</sec>
			<sec sec-type="methods">
				<title>Métodos</title>
				<sec>
					<title>Desenho do estudo e participantes</title>
					<p>Este estudo de coorte retrospectivo, unicêntrico e de braço único utilizou registros médicos eletrônicos e imagens de PET-CT para avaliar pacientes com câncer de pulmão que iniciaram tratamento com ICIs entre julho de 2016 e dezembro de 2021. Os critérios de inclusão foram: idade igual ou superior a 18 anos, diagnóstico de câncer de pulmão tratado com ICIs (inibidores de proteína 4 associada a linfócitos T citotóxicos – CTLA-4, de <italic>Programmed Death</italic> 1 PD-1 ou de <italic>Programmed Death Ligand</italic> 1 PD-L1) e realização de pelo menos duas varreduras de PET-CT, sendo uma no início do estudo e outra durante o curso do tratamento.</p>
					<p>O objetivo primário do estudo foi avaliar a variação na taxa de captação de MGU, medida pela ΔSUV, durante a administração de ICIs e seu impacto nos desfechos de sobrevivência. Os objetivos secundários incluíram a investigação de potenciais efeitos positivos ou negativos associados ao tabagismo, diabetes, hipertensão, uso de metformina e uso de BB nos desfechos de sobrevivência.</p>
					<p>A aprovação ética para esta pesquisa foi concedida pelo comitê de ética, sob o número de registro CAAE 47402321.9.0000.5186.</p>
				</sec>
				<sec>
					<title>Análise estatística</title>
					<p>As estatísticas descritivas para variáveis numéricas foram apresentadas como mediana e intervalo interquartil, enquanto variáveis categóricas foram descritas em frequências absolutas e relativas. O teste de Mann-Whitney foi utilizado para comparar as medianas entre os grupos. A PFS e a SG foram estimadas pelo método de Kaplan-Meier, e o teste de <italic>log-rank</italic> foi aplicado para a comparação das curvas de sobrevivência. O nível de significância (alfa) foi estabelecido em 0,05.</p>
				</sec>
			</sec>
			<sec sec-type="results">
				<title>Resultados</title>
				<p>Entre os 114 pacientes com câncer de pulmão submetidos à imunoterapia em nosso centro médico, 58 atenderam aos critérios de inclusão. Desses, 25 eram mulheres e 33 homens, com idade mediana de 68 anos (desvio padrão [DP] ±10). O índice de massa corporal (IMC) mediano foi de 26 (DP ±4), e o intervalo mediano entre a PET basal e o início do tratamento foi de 27 dias (DP ±47).</p>
				<p>Quase 52% dos pacientes receberam imunoterapia combinada com quimioterapia, enquanto os 48% restantes foram tratados com imunoterapia isoladamente. Na amostra, 31 pacientes (53,45%) apresentaram ΔSUV positiva, indicando um aumento na MGU. Por outro lado, 25 pacientes (43,10%) exibiram ΔSUV negativa, indicando uma redução na MGU. Dois pacientes (3,45%) não apresentaram variação no SUV e foram excluídos da análise de subgrupos. Os subgrupos com ΔSUV positiva e negativo foram comparáveis, exceto pelo intervalo prolongado entre a tomografia PET basal e o início do tratamento observado no grupo com ΔSUV negativa. Dados clínicos e demográficos detalhados estão apresentados na <xref ref-type="table" rid="t3">Tabela 1</xref>, enquanto a <xref ref-type="table" rid="t4">Tabela 2</xref> exibe as características histológicas e de tratamento da população do estudo.</p>
				<table-wrap id="t3">
					<label>Tabela 1</label>
					<caption>
						<title>Características demográficas e distribuição por subgrupos da população do estudo (n = 58), subgrupos +δSUV e –δSUV.</title>
					</caption>
					<table frame="hsides" rules="none">
						<colgroup width="14%">
							<col/>
							<col/>
							<col/>
							<col/>
							<col/>
							<col/>
							<col/>
						</colgroup>
						<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
							<tr style="background-color:#C58874">
								<th align="left" valign="middle"/>
								<th align="center" colspan="2" valign="middle">População geral do estudo</th>
								<th align="center" colspan="2" valign="middle">ΔSUV+</th>
								<th align="center" colspan="2" valign="middle">ΔSUV–</th>
							</tr>
							<tr style="background-color:#C58874">
								<th align="left" valign="middle"/>
								<th align="center" valign="middle">Mediana</th>
								<th align="center" valign="middle">DP</th>
								<th align="center" colspan="2" valign="middle">Mediana</th>
								<th align="center" colspan="2" valign="middle">Mediana</th>
							</tr>
						</thead>
						<tbody style="border-bottom: thin solid; border-color: #000000">
							<tr>
								<td align="left" valign="middle"><bold>Idade, anos</bold></td>
								<td align="center" valign="middle">68</td>
								<td align="center" valign="middle">±10</td>
								<td align="center" colspan="2" valign="middle">67,0096</td>
								<td align="center" colspan="2" valign="middle">68,5336</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle"><bold>IMC, kg/m</bold><sup>2</sup></td>
								<td align="center" valign="middle">26</td>
								<td align="center" valign="middle">±4</td>
								<td align="center" colspan="2" valign="middle">26,01</td>
								<td align="center" colspan="2" valign="middle">26,26</td>
							</tr>
							<tr>
								<td align="left" valign="middle"><bold>Intervalo entre o PET basal e o início do tratamento, dias</bold></td>
								<td align="center" valign="middle">27</td>
								<td align="center" valign="middle">±47</td>
								<td align="center" colspan="2" valign="middle">31,58</td>
								<td align="center" colspan="2" valign="middle">52,52</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle"><bold>Sexo</bold></td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Feminino</td>
								<td align="center" valign="middle">25</td>
								<td align="center" valign="middle">43</td>
								<td align="center" valign="middle">14</td>
								<td align="center" valign="middle">45,16</td>
								<td align="center" valign="middle">10</td>
								<td align="center" valign="middle">40</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Masculino</td>
								<td align="center" valign="middle">33</td>
								<td align="center" valign="middle">57</td>
								<td align="center" valign="middle">17</td>
								<td align="center" valign="middle">54,84</td>
								<td align="center" valign="middle">15</td>
								<td align="center" valign="middle">60</td>
							</tr>
							<tr>
								<td align="left" valign="middle"><bold>Comorbidades</bold></td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
							</tr>
							<tr>
								<td align="left" valign="middle">Hipertensão</td>
								<td align="center" valign="middle">28</td>
								<td align="center" valign="middle">48</td>
								<td align="center" valign="middle">14</td>
								<td align="center" valign="middle">45,16</td>
								<td align="center" valign="middle">12</td>
								<td align="center" valign="middle">48</td>
							</tr>
							<tr>
								<td align="left" valign="middle">Diabetes</td>
								<td align="center" valign="middle">12</td>
								<td align="center" valign="middle">21</td>
								<td align="center" valign="middle">5</td>
								<td align="center" valign="middle">16,12</td>
								<td align="center" valign="middle">7</td>
								<td align="center" valign="middle">28</td>
							</tr>
							<tr>
								<td align="left" valign="middle">Tabagismo</td>
								<td align="center" valign="middle">43</td>
								<td align="center" valign="middle">74</td>
								<td align="center" valign="middle">21</td>
								<td align="center" valign="middle">67,74</td>
								<td align="center" valign="middle">20</td>
								<td align="center" valign="middle">80</td>
							</tr>
							<tr>
								<td align="left" valign="middle">Doença coronariana</td>
								<td align="center" valign="middle">4</td>
								<td align="center" valign="middle">7</td>
								<td align="center" valign="middle">2</td>
								<td align="center" valign="middle">6,45</td>
								<td align="center" valign="middle">2</td>
								<td align="center" valign="middle">8</td>
							</tr>
							<tr>
								<td align="left" valign="middle">IC</td>
								<td align="center" valign="middle">1</td>
								<td align="center" valign="middle">2</td>
								<td align="center" valign="middle">0</td>
								<td align="center" valign="middle">0</td>
								<td align="center" valign="middle">1</td>
								<td align="center" valign="middle">4</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle"><bold>Uso de medicamentos</bold></td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">BBs</td>
								<td align="center" valign="middle">14</td>
								<td align="center" valign="middle">24</td>
								<td align="center" valign="middle">7</td>
								<td align="center" valign="middle">22,58</td>
								<td align="center" valign="middle">6</td>
								<td align="center" valign="middle">24</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Inibidores da ECA/BRA</td>
								<td align="center" valign="middle">17</td>
								<td align="center" valign="middle">29</td>
								<td align="center" valign="middle">9</td>
								<td align="center" valign="middle">29,03</td>
								<td align="center" valign="middle">7</td>
								<td align="center" valign="middle">28</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Metformina</td>
								<td align="center" valign="middle">8</td>
								<td align="center" valign="middle">14</td>
								<td align="center" valign="middle">3</td>
								<td align="center" valign="middle">9,68</td>
								<td align="center" valign="middle">4</td>
								<td align="center" valign="middle">16</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Anticoagulantes</td>
								<td align="center" valign="middle">3</td>
								<td align="center" valign="middle">5</td>
								<td align="center" valign="middle">3</td>
								<td align="center" valign="middle">9,68</td>
								<td align="center" valign="middle">0</td>
								<td align="center" valign="middle">0</td>
							</tr>
						</tbody>
					</table>
					<table-wrap-foot>
						<fn id="TFN3">
							<p>SUV: Variação do Valor e Captação Padronizado; DP: desvio padrão; IMC: índice de massa corporal; PET: tomografia por emissão de pósitrons combinada à tomografia computadorizada; IC: insuficiência cardíaca; BB: β-bloqueadores; ECA/BRA: enzima conversora da angiotensina (ECA)/bloqueadores dos receptores da angiotensina II.</p>
						</fn>
					</table-wrap-foot>
				</table-wrap>
				<table-wrap id="t4">
					<label>Tabela 2</label>
					<caption>
						<title>Características histológicas e de tratamento da população do estudo.</title>
					</caption>
					<table frame="hsides" rules="none">
						<colgroup width="14%">
							<col/>
							<col/>
							<col/>
							<col/>
							<col/>
							<col/>
							<col/>
						</colgroup>
						<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
							<tr style="background-color:#C58874">
								<th align="left" valign="middle"/>
								<th align="center" colspan="2" valign="middle">População geral do estudo</th>
								<th align="center" colspan="2" valign="middle">ΔSUV+</th>
								<th align="center" colspan="2" valign="middle">ΔSUV–</th>
							</tr>
						</thead>
						<tbody style="border-bottom: thin solid; border-color: #000000">
							<tr>
								<td align="left" valign="middle">Histologia</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
							</tr>
							<tr>
								<td align="left" valign="middle">Adenocarcinoma</td>
								<td align="center" valign="middle">43</td>
								<td align="center" valign="middle">74</td>
								<td align="center" valign="middle">23</td>
								<td align="center" valign="middle">74,19</td>
								<td align="center" valign="middle">18</td>
								<td align="center" valign="middle">72</td>
							</tr>
							<tr>
								<td align="left" valign="middle">CEC</td>
								<td align="center" valign="middle">4</td>
								<td align="center" valign="middle">7</td>
								<td align="center" valign="middle">2</td>
								<td align="center" valign="middle">6,45</td>
								<td align="center" valign="middle">2</td>
								<td align="center" valign="middle">8</td>
							</tr>
							<tr>
								<td align="left" valign="middle">CPCNP</td>
								<td align="center" valign="middle">5</td>
								<td align="center" valign="middle">9</td>
								<td align="center" valign="middle">2</td>
								<td align="center" valign="middle">6,45</td>
								<td align="center" valign="middle">2</td>
								<td align="center" valign="middle">8</td>
							</tr>
							<tr>
								<td align="left" valign="middle">Outros</td>
								<td align="center" valign="middle">6</td>
								<td align="center" valign="middle">10</td>
								<td align="center" valign="middle">4</td>
								<td align="center" valign="middle">12,9</td>
								<td align="center" valign="middle">3</td>
								<td align="center" valign="middle">12</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Imunoterapia</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Atezolizumabe</td>
								<td align="center" valign="middle">14</td>
								<td align="center" valign="middle">24</td>
								<td align="center" valign="middle">6</td>
								<td align="center" valign="middle">19,35</td>
								<td align="center" valign="middle">8</td>
								<td align="center" valign="middle">32</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Durvalumabe</td>
								<td align="center" valign="middle">5</td>
								<td align="center" valign="middle">9</td>
								<td align="center" valign="middle">3</td>
								<td align="center" valign="middle">9,68</td>
								<td align="center" valign="middle">1</td>
								<td align="center" valign="middle">4</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Nivolumabe</td>
								<td align="center" valign="middle">13</td>
								<td align="center" valign="middle">22</td>
								<td align="center" valign="middle">7</td>
								<td align="center" valign="middle">22,58</td>
								<td align="center" valign="middle">6</td>
								<td align="center" valign="middle">24</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Pembrolizumabe</td>
								<td align="center" valign="middle">26</td>
								<td align="center" valign="middle">45</td>
								<td align="center" valign="middle">15</td>
								<td align="center" valign="middle">48,38</td>
								<td align="center" valign="middle">10</td>
								<td align="center" valign="middle">40</td>
							</tr>
							<tr>
								<td align="left" valign="middle">Tipo de tratamento</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
							</tr>
							<tr>
								<td align="left" valign="middle">QT-IO</td>
								<td align="center" valign="middle">30</td>
								<td align="center" valign="middle">52</td>
								<td align="center" valign="middle">17</td>
								<td align="center" valign="middle">54,84</td>
								<td align="center" valign="middle">12</td>
								<td align="center" valign="middle">48</td>
							</tr>
							<tr>
								<td align="left" valign="middle">IO</td>
								<td align="center" valign="middle">28</td>
								<td align="center" valign="middle">48</td>
								<td align="center" valign="middle">14</td>
								<td align="center" valign="middle">45,16</td>
								<td align="center" valign="middle">13</td>
								<td align="center" valign="middle">52</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Linha de tratamento</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">1ª linha</td>
								<td align="center" valign="middle">35</td>
								<td align="center" valign="middle">60</td>
								<td align="center" valign="middle">19</td>
								<td align="center" valign="middle">61,29</td>
								<td align="center" valign="middle">14</td>
								<td align="center" valign="middle">56</td>
							</tr>
							<tr style="background-color:#E8CCBF">
								<td align="left" valign="middle">Linhas subsequentes</td>
								<td align="center" valign="middle">23</td>
								<td align="center" valign="middle">40</td>
								<td align="center" valign="middle">12</td>
								<td align="center" valign="middle">38,71</td>
								<td align="center" valign="middle">11</td>
								<td align="center" valign="middle">44</td>
							</tr>
							<tr>
								<td align="left" valign="middle">Análise genética do tumor</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
								<td align="center" valign="middle">N</td>
								<td align="center" valign="middle">%</td>
							</tr>
							<tr>
								<td align="left" valign="middle">ALK/EGFR</td>
								<td align="center" valign="middle">9</td>
								<td align="center" valign="middle">15</td>
								<td align="center" valign="middle">4</td>
								<td align="center" valign="middle">12,9</td>
								<td align="center" valign="middle">4</td>
								<td align="center" valign="middle">16</td>
							</tr>
							<tr>
								<td align="left" valign="middle">Sem mutação</td>
								<td align="center" valign="middle">23</td>
								<td align="center" valign="middle">40</td>
								<td align="center" valign="middle">14</td>
								<td align="center" valign="middle">45,16</td>
								<td align="center" valign="middle">10</td>
								<td align="center" valign="middle">40</td>
							</tr>
							<tr>
								<td align="left" valign="middle">Desconhecido</td>
								<td align="center" valign="middle">26</td>
								<td align="center" valign="middle">45</td>
								<td align="center" valign="middle">13</td>
								<td align="center" valign="middle">41,94</td>
								<td align="center" valign="middle">11</td>
								<td align="center" valign="middle">44</td>
							</tr>
							<tr>
								<td align="left" valign="middle">PD-L1: &gt;50%</td>
								<td align="center" valign="middle">8</td>
								<td align="center" valign="middle">14</td>
								<td align="center" valign="middle">3</td>
								<td align="center" valign="middle">9,68</td>
								<td align="center" valign="middle">4</td>
								<td align="center" valign="middle">16</td>
							</tr>
							<tr>
								<td align="left" valign="middle">PD-L1: 1%–50%</td>
								<td align="center" valign="middle">9</td>
								<td align="center" valign="middle">15</td>
								<td align="center" valign="middle">8</td>
								<td align="center" valign="middle">25,81</td>
								<td align="center" valign="middle">1</td>
								<td align="center" valign="middle">4</td>
							</tr>
							<tr>
								<td align="left" valign="middle">PD-L1: &lt;1%</td>
								<td align="center" valign="middle">10</td>
								<td align="center" valign="middle">17</td>
								<td align="center" valign="middle">6</td>
								<td align="center" valign="middle">19,35</td>
								<td align="center" valign="middle">7</td>
								<td align="center" valign="middle">28</td>
							</tr>
							<tr>
								<td align="left" valign="middle">PD-L1: desconhecido</td>
								<td align="center" valign="middle">31</td>
								<td align="center" valign="middle">53</td>
								<td align="center" valign="middle">14</td>
								<td align="center" valign="middle">45,16</td>
								<td align="center" valign="middle">13</td>
								<td align="center" valign="middle">52</td>
							</tr>
						</tbody>
					</table>
					<table-wrap-foot>
						<fn id="TFN4">
							<p>SUV: Variação do Valor e Captação Padronizado; CEC: Carcinoma espinocelular; PD-L1: Programmed Death Ligand 1; CPCNP: câncer de pulmão de células não pequenas; QT-IO: Quimioterapia em combinação com Imunoterapia; ALK/EGFR: Mutação da Quinase do Linfoma Anaplástico (ALK) ou do Receptor do Fator de Crescimento Epidérmico (EGFR).</p>
						</fn>
					</table-wrap-foot>
				</table-wrap>
				<p>Entre as comorbidades documentadas, a maior prevalência foi de tabagismo (74%), seguida por hipertensão (48%) e diabetes (21%). Os medicamentos mais frequentemente utilizados foram inibidores da enzima conversora da angiotensina (ECA) ou bloqueadores dos receptores da angiotensina II (BRA) (29%), BBs (24%) e metformina (14%).</p>
				<p>Em relação ao desfecho primário, a mediana geral da ΔSUV foi de +0,05. No grupo com controle da doença, a mediana da ΔSUV foi de +0,48, indicando um aumento na MGU. Em contraste, o grupo com progressão da doença apresentou uma mediana da ΔSUV de −0,66.</p>
				<p>Ao comparar pacientes com ΔSUV miocárdica positiva com aqueles com ΔSUV negativa, observou-se um prolongamento mediano de 161 dias na SLP em favor do grupo com ΔSUV miocárdica positiva (p = 0,066). Além disso, foi registrado um aumento de 281 dias na SG no grupo com ΔSUV miocárdica positiva (p = 0,256) (<xref ref-type="fig" rid="f5">Figura 1</xref>).</p>
				<fig id="f5">
					<label>Figura 1</label>
					<caption>
						<title>Papel da MGU como ferramenta de avaliação de prognóstico e resposta, e o efeito da metformina e BBs na sobrevida em imunoterapia. ICI: inibidores de checkpoint imunológicos; MGU: FDG miocárdica; PET-CT: emissão de pósitrons combinada à tomografia computadorizada; SG: sobrevida global; SLP: sobrevida livre de progressão; SUV: valor de captação padronizado.</title>
					</caption>
					<graphic xlink:href="2675-312X-abcimg-38-01-e20240108-gf01-pt.tif"/>
				</fig>
				<p>Além disso, pacientes diabéticos apresentaram um aumento significativo de 759 dias na SG (p = 0,023). Na análise de subgrupos, foi observada uma tendência para resultados ainda mais favoráveis entre os usuários de metformina (p = 0,015) (<xref ref-type="fig" rid="f6">Figura 2</xref>). Adicionalmente, uma tendência não estatisticamente significativa de prolongamento de 285 dias na SG foi identificada entre os usuários de BB (p = 0,886) (<xref ref-type="fig" rid="f7">Figura 3</xref>).</p>
				<fig id="f6">
					<label>Figura 2</label>
					<caption>
						<title>Comparação de SG entre usuários de metformina e não usuários de metformina.</title>
					</caption>
					<graphic xlink:href="2675-312X-abcimg-38-01-e20240108-gf02-pt.tif"/>
				</fig>
				<fig id="f7">
					<label>Figura 3</label>
					<caption>
						<title>Comparação de SG entre usuários de BBs e não usuários de BBs. BB: β-bloqueadores.</title>
					</caption>
					<graphic xlink:href="2675-312X-abcimg-38-01-e20240108-gf03-pt.tif"/>
				</fig>
				<p>Entretanto, não foram identificadas associações estatisticamente significativas entre o uso de inibidores da ECA ou BRA, tabagismo ou hipertensão com a SG ou a SLP.</p>
			</sec>
			<sec sec-type="discussion">
				<title>Discussão</title>
				<p>A capacidade bem documentada da PET-CT com Fluorodeoxiglicose F 18 (18F-FDG) de identificar inflamação tecidual — uma característica marcante das reações adversas imunomediadas (RAim) — aponta para seu potencial na detecção precoce de RAim subclínicas. Além disso, a PET-CT pode desempenhar um papel crucial na confirmação de suspeitas de RAim, como miocardite, ao revelar aumentos heterogêneos e moderados a altos na captação de 18F-FDG no ventrículo esquerdo (VE).<sup><xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref></sup></p>
				<p>A disparidade observada na ΔSUV cardíaca média entre o grupo com controle da doença e o grupo com progressão da doença em nosso estudo sugere uma associação potencial entre o aumento do SUV após o tratamento e respostas melhoradas à imunoterapia. Essa descoberta é corroborada pelo prolongamento mediano de 161 dias na SLP (p = 0,066) e 281 dias na SG (p = 0,256) entre os pacientes que apresentaram ΔSUV positiva. Esses resultados destacam o potencial da ΔSUV como um marcador preditivo de resposta ao tratamento e prognóstico em pacientes submetidos à imunoterapia.</p>
				<p>Embora o mecanismo preciso subjacente aos RAim ainda não seja totalmente compreendido, sabe-se que os ICIs aumentam a resposta imune contra tumores, o que pode levar a efeitos colaterais inflamatórios devido ao reconhecimento de antígenos compartilhados entre células tumorais e tecidos normais. Assim, é hipotetizado que o aumento na captação de 18F-FDG, característico de processos inflamatórios, associado à presença de RAim, poderia estimar a resposta à imunoterapia e estar relacionado a resultados clínicos positivos.</p>
				<p>Nossas descobertas estão alinhadas com uma revisão sistemática e meta-análise recentes, que demonstraram uma correlação entre as RAim e melhora na SG, na SLP e nas taxas de resposta objetiva (<italic>objective response rates</italic> – ORRs) em pacientes tratados com ICI. O aumento no SUV foi identificado como o principal marcador de RAim na PET-CT.<sup><xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B19">19</xref></sup> Da mesma forma, foi observado que pacientes que apresentaram RAim de baixo a médio grau durante regimes de tratamento com atezolizumabe exibiram uma SG mais longa em comparação com aqueles com RAim de alto grau ou nenhum RAim.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> Essas descobertas reforçam ainda mais a ideia de que a ocorrência de RAim, juntamente com alterações na MGU, pode servir como um valioso indicador prognóstico e preditor de resposta ao tratamento em pacientes submetidos à imunoterapia.</p>
				<p>Foi observada uma correlação significativa entre o aumento da SG e o uso de metformina (p = 0,015). A relação entre metformina e imunidade ao câncer foi postulada para envolver vários mecanismos. Estes incluem a ativação de vias de sinalização dependentes de adenosina monofosfato-ativada proteína quinase (AMPK) e independentes de AMPK, que exercem efeitos antitumorais, além da elevação do limiar de exaustão de linfócitos T citotóxicos (LCT), aumentando, assim, a vigilância imunológica. Além disso, a metformina demonstrou impedir a sinalização imunoinibitória de PD-L1 por meio da fosforilação de PD-L1 associada à ativação de sinalização dependente de AMPK,<sup><xref ref-type="bibr" rid="B21">21</xref></sup> bem como a glicosilação e degradação de PD-L1 dentro do retículo endoplasmático.<sup><xref ref-type="bibr" rid="B22">22</xref></sup> Essas descobertas apoiam o papel potencial da metformina como um modulador da imunidade ao câncer e sugerem seus benefícios potenciais na melhoria dos resultados dos pacientes, particularmente em termos de SG.</p>
				<p>Consistente com nossas descobertas, vários estudos demonstraram resultados de tratamento aprimorados quando ICIs são combinados com metformina em modelos pré-clínicos de melanoma metastático,<sup><xref ref-type="bibr" rid="B23">23</xref></sup> câncer de pulmão de células não pequenas (CPCNP)<sup><xref ref-type="bibr" rid="B24">24</xref></sup> e câncer de mama.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> Esses estudos fornecem evidências adicionais que apoiam os potenciais efeitos sinérgicos da combinação de ICIs com metformina, levando a respostas terapêuticas aprimoradas em vários tipos de câncer.</p>
				<p>Além disso, a combinação de metformina com bloqueio de PD-1 mostrou resultados promissores no aumento da depuração do tumor e na melhora da função das células T ao mitigar a hipóxia induzida pelo tumor, que atua como um fator inibitório para a atividade das células T.<sup><xref ref-type="bibr" rid="B25">25</xref></sup> Além disso, em modelos murinos, o efeito sinérgico da metformina e da imunoterapia com vacina demonstrou reduzir a expressão de PD-L1 em células tumorais.<sup><xref ref-type="bibr" rid="B11">11</xref></sup> Essas descobertas destacam o potencial da metformina na modulação do microambiente tumoral, aliviando a supressão imunológica associada à hipóxia e aumentando a eficácia das abordagens imunoterapêuticas.</p>
				<p>Da mesma forma, investigações examinaram o potencial de combinar metformina com monoterapia anti-PD-1 ou uma combinação de anti-VEGFR2 e anti-PD-1 para restaurar a sensibilidade a imunoterapias em tumores de Esteato-hepatite Não Alcoólica-Carcinoma Hepatocelular (EHNA-CHC), que são tipicamente caracterizados por responsividade limitada. Notavelmente, esses estudos conduzidos em camundongos demonstraram a eficácia terapêutica aprimorada alcançada por meio de tais combinações, fornecendo suporte adicional para explorar os efeitos sinérgicos da metformina e imunoterapias na superação da resistência e na melhoria dos resultados do tratamento em tipos de tumores desafiadores.<sup><xref ref-type="bibr" rid="B26">26</xref>,<xref ref-type="bibr" rid="B27">27</xref></sup></p>
				<p>Embora limitados em número, os estudos disponíveis que investigam a combinação de metformina e ICIs em humanos produziram resultados promissores. Em um estudo italiano envolvendo 40 pacientes, a administração concomitante de metformina e nivolumabe foi bem tolerada e considerada segura. Notavelmente, doses mais altas de metformina (&gt; 1.000 mg/dia) foram associadas a SG mais longa (p = 0,037) e SLP (p = 0,021) e taxas de resposta melhoradas, corroborando nossas próprias descobertas.<sup><xref ref-type="bibr" rid="B28">28</xref></sup> Da mesma forma, a combinação de metformina com ICIs demonstrou resultados clínicos potencialmente favoráveis, embora a significância estatística não tenha sido alcançada, provavelmente devido ao pequeno tamanho da amostra.<sup><xref ref-type="bibr" rid="B23">23</xref></sup> Além disso, a metformina demonstrou melhorar as funções das células assassinas naturais no carcinoma de células escamosas de cabeça e pescoço.<sup><xref ref-type="bibr" rid="B29">29</xref></sup> Essas descobertas preliminares sugerem que a combinação de metformina com ICIs é promissora como estratégia terapêutica, garantindo mais investigação em estudos clínicos maiores para estabelecer sua eficácia e perfil de segurança em humanos.</p>
				<p>Portanto, com base na multiplicidade de vias e mecanismos imunológicos propostos em estudos pré-clínicos e seus resultados favoráveis, pode-se concluir razoavelmente que a metformina pode desempenhar um papel significativo como uma terapia adjuvante segura, bem tolerada e prontamente disponível no tratamento de cânceres sólidos quando usada em conjunto com ICIs.</p>
				<p>O papel potencial dos BBs no tratamento do câncer tem sido amplamente investigado, com evidências conflitantes encontradas na literatura. Alguns estudos retrospectivos mais antigos demonstraram melhores resultados de tratamento em pacientes com câncer de mama, especialmente em triplo-negativo,<sup><xref ref-type="bibr" rid="B30">30</xref>,<xref ref-type="bibr" rid="B31">31</xref></sup> câncer de ovário,<sup><xref ref-type="bibr" rid="B32">32</xref></sup> bexiga<sup><xref ref-type="bibr" rid="B33">33</xref></sup> e CPCNP.<sup><xref ref-type="bibr" rid="B34">34</xref></sup></p>
				<p>Além disso, um possível mecanismo de ação para os BBs no câncer foi proposto na literatura, no qual a sinalização beta-adrenérgica foi relacionada à redução da proliferação de células T CD8+ e à imunossupressão mediada por células T reguladoras e células supressoras derivadas de mieloides.<sup><xref ref-type="bibr" rid="B10">10</xref></sup></p>
				<p>Embora os dados observados sobre o uso de BBs e a SG não tenham alcançado significância estatística, possivelmente devido ao tamanho limitado da amostra, a tendência em direção a um aumento de 285 dias na SG sugere um possível papel para os BBs como terapia adjuvante para os ICIs no tratamento do câncer. Estudos adicionais com amostras maiores são necessários para elucidar o mecanismo de ação subjacente e determinar se os BBs devem ser considerados como uma terapia complementar para todos os pacientes submetidos ao bloqueio de <italic>checkpoint</italic> imunológico.</p>
				<p>Apesar das evidências conflitantes na literatura sobre o impacto dos BBs na SG, na SLP e nas ORRs, descobertas semelhantes às nossas foram relatadas em uma meta-análise recente que incluiu 10.156 pacientes. A meta-análise revelou que o uso de BBs foi associado a melhores ORRs para os ICIs (<italic>odds ratio</italic> [OR] = 0,42 [0,19-0,94], p = 0,036), particularmente no subgrupo de pacientes com câncer de pulmão (OR = 0,25 [0,08-0,83], p = 0,024). No entanto, nenhuma associação significativa foi encontrada entre o uso de BBs e SG ou SLP na análise combinada.<sup><xref ref-type="bibr" rid="B29">29</xref></sup></p>
				<p>Em resumo, embora a literatura sobre a relação entre BBs e os resultados do tratamento do câncer permaneça inconclusiva, nossas descobertas, juntamente com os resultados da meta-análise, sugerem que os BBs podem ter um papel potencial como terapia adjuvante aos ICIs no tratamento do câncer, o que justifica a realização de estudos adicionais para explorar essa possibilidade.</p>
				<sec>
					<title>Limitações do estudo</title>
					<p>O estudo apresenta algumas limitações que devem ser reconhecidas. Primeiramente, o tamanho da amostra foi relativamente pequeno, principalmente devido ao número limitado de pacientes com câncer de pulmão que receberam terapia com ICI em nosso centro. Consequentemente, a significância estatística de alguns dos achados pode estar comprometida. Mais pesquisas envolvendo coortes maiores são essenciais para fortalecer a validade e a generalização dos nossos resultados.</p>
					<p>Além disso, investigações adicionais são necessárias para estabelecer os mecanismos de ação subjacentes e determinar a significância clínica do uso de BBs em combinação com ICIs. A importância da ΔSUV nos resultados de sobrevivência também deve ser explorada em estudos futuros. Esses aspectos fornecerão uma compreensão mais abrangente do potencial terapêutico e das implicações prognósticas associadas ao uso combinado de metformina, BBs e ICIs no tratamento do câncer de pulmão.</p>
				</sec>
			</sec>
			<sec sec-type="conclusions">
				<title>Conclusões</title>
				<p>Embora estudos adicionais sejam necessários para avaliar de forma abrangente a relação entre o aumento da MGU e melhores resultados em pacientes submetidos à terapia com ICIs, o papel da PET-CT como uma ferramenta valiosa para avaliar a resposta ao tratamento e os RAim está bem estabelecido. Nossas descobertas destacam uma associação significativa entre o aumento da SG e o uso de metformina. Isso sugere que a metformina pode ser uma importante opção de tratamento adjuvante para pacientes em terapia com ICIs, independentemente de seu estado diabético ou hiperglicêmico. Os efeitos sinérgicos da metformina por meio de múltiplas vias, juntamente com sua acessibilidade, efeitos colaterais mínimos e perfil de segurança favorável, ressaltam seu potencial para melhorar os resultados do tratamento.</p>
			</sec>
		</body>
		<back>
			<fn-group>
				<fn fn-type="financial-disclosure" id="fn4">
					<label>Fontes de Financiamento</label>
					<p>O presente estudo não teve fontes de financiamento externas.</p>
				</fn>
				<fn fn-type="other" id="fn5">
					<label>Vinculação Acadêmica</label>
					<p>Não há vinculação deste estudo a programas de pós-graduação.</p>
				</fn>
				<fn fn-type="other" id="fn6">
					<label>Aprovação Ética e Consentimento Informado</label>
					<p>Este estudo foi aprovado pelo Comitê de Ética do Secretaria de Saúde do Estado da Paraíba – SES/PB sob o número de protocolo 47402321.9.0000.5186. Todos os procedimentos envolvidos nesse estudo estão de acordo com a Declaração de Helsinki de 1975, atualizada em 2013. O consentimento informado foi obtido de todos os participantes incluídos no estudo.</p>
				</fn>
			</fn-group>
		</back>
	</sub-article>
</article>