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array:24 [ "pii" => "S2253808920301154" "issn" => "22538089" "doi" => "10.1016/j.remnie.2020.06.016" "estado" => "S300" "fechaPublicacion" => "2021-09-01" "aid" => "1204" "copyright" => "Sociedad Española de Medicina Nuclear e Imagen Molecular" "copyrightAnyo" => "2020" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Rev Esp Med Nucl Imagen Mol. 2021;40:281-6" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "Traduccion" => array:1 [ "es" => array:19 [ "pii" => "S2253654X20301311" "issn" => "2253654X" "doi" => "10.1016/j.remn.2020.06.022" "estado" => "S300" "fechaPublicacion" => "2021-09-01" "aid" => "1204" "copyright" => "Sociedad Española de Medicina Nuclear e Imagen Molecular" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Rev Esp Med Nucl Imagen Mol. 2021;40:281-6" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "es" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original</span>" "titulo" => "El análisis semicuantitativo de la PET con [<span class="elsevierStyleSup">18</span>F]FDG interim es superior para predecir la evolución en los pacientes con linfoma de Hodgkin en comparación con el análisis visual" "tienePdf" => "es" "tieneTextoCompleto" => "es" "tieneResumen" => array:2 [ 0 => "es" 1 => "en" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "281" "paginaFinal" => "286" ] ] "titulosAlternativos" => array:1 [ "en" => array:1 [ "titulo" => "Semiquantitative analysis of interim <span class="elsevierStyleSup">18</span>F-FDG PET is superior in predicting outcome in Hodgkin lymphoma patients compared to visual analysis" ] ] "contieneResumen" => array:2 [ "es" => true "en" => true ] "contieneTextoCompleto" => array:1 [ "es" => true ] "contienePdf" => array:1 [ "es" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figura 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1908 "Ancho" => 2500 "Tamanyo" => 183351 ] ] "descripcion" => array:1 [ "es" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Curvas de supervivencia libres de progresión de los pacientes con LH según el resultado de la exploración PETi en función de lo evaluado por los cinco métodos diferentes que se analizan (arriba a la izquierda: DeltaSUV<span class="elsevierStyleInf">máx</span>, arriba a la derecha: DeltaSUV<span class="elsevierStyleInf">pico</span>, abajo-izquierda: DeltaMTV, abajo-derecha: DeltaTLG).</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Teresa Ribeiro, Ana Marques, Gonçalo Ferreira, Clara Castro, Márcio Tavares, Ana Espírito-Santo, Cláudia Moreira, José Mariz" "autores" => array:8 [ 0 => array:2 [ "nombre" => "Teresa" "apellidos" => "Ribeiro" ] 1 => array:2 [ "nombre" => "Ana" "apellidos" => "Marques" ] 2 => array:2 [ "nombre" => "Gonçalo" "apellidos" => "Ferreira" ] 3 => array:2 [ "nombre" => "Clara" "apellidos" => "Castro" ] 4 => array:2 [ "nombre" => "Márcio" "apellidos" => "Tavares" ] 5 => array:2 [ "nombre" => "Ana" "apellidos" => "Espírito-Santo" ] 6 => array:2 [ "nombre" => "Cláudia" "apellidos" => "Moreira" ] 7 => array:2 [ "nombre" => "José" "apellidos" => "Mariz" ] ] ] ] ] "idiomaDefecto" => "es" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S2253808920301154" "doi" => "10.1016/j.remnie.2020.06.016" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2253808920301154?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2253654X20301311?idApp=UINPBA00004N" "url" => "/2253654X/0000004000000005/v1_202108200653/S2253654X20301311/v1_202108200653/es/main.assets" ] ] "itemSiguiente" => array:19 [ "pii" => "S2253808920301142" "issn" => "22538089" "doi" => "10.1016/j.remnie.2020.09.010" "estado" => "S300" "fechaPublicacion" => "2021-09-01" "aid" => "1201" "copyright" => "Sociedad Española de Medicina Nuclear e Imagen Molecular" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Rev Esp Med Nucl Imagen Mol. 2021;40:287-92" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "en" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original Article</span>" "titulo" => "Tumor markers and <span class="elsevierStyleSup">18</span>F-FDG PET/CT after orchiectomy in seminoma: Is there any correlation?" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "287" "paginaFinal" => "292" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Marcadores tumorales y <span class="elsevierStyleSup">18</span>F-FDG PET/CT después de orquiectomía en seminoma: ¿hay alguna correlación?" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 2351 "Ancho" => 2500 "Tamanyo" => 238597 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">MIP (a), axial CT (b), axial PET (c) and axial fused PET/CT (d) images of a <span class="elsevierStyleSup">18</span>F-FDG PET/CT scan demonstrating a metastatic lesion on the posterior arch of the 8th right rib in a patient with positive hCG and negative AFP.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Francesco Dondi, Domenico Albano, Francesco Bertagna, Raffaele Giubbini" "autores" => array:4 [ 0 => array:2 [ "nombre" => "Francesco" "apellidos" => "Dondi" ] 1 => array:2 [ "nombre" => "Domenico" "apellidos" => "Albano" ] 2 => array:2 [ "nombre" => "Francesco" "apellidos" => "Bertagna" ] 3 => array:2 [ "nombre" => "Raffaele" "apellidos" => "Giubbini" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "es" => array:9 [ "pii" => "S2253654X20301281" "doi" => "10.1016/j.remn.2020.06.019" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2253654X20301281?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2253808920301142?idApp=UINPBA00004N" "url" => "/22538089/0000004000000005/v1_202108210518/S2253808920301142/v1_202108210518/en/main.assets" ] "itemAnterior" => array:19 [ "pii" => "S2253808920301191" "issn" => "22538089" "doi" => "10.1016/j.remnie.2020.09.014" "estado" => "S300" "fechaPublicacion" => "2021-09-01" "aid" => "1209" "copyright" => "Sociedad Española de Medicina Nuclear e Imagen Molecular" "documento" => "article" "crossmark" => 0 "subdocumento" => "fla" "cita" => "Rev Esp Med Nucl Imagen Mol. 2021;40:275-80" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "en" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original Article</span>" "titulo" => "Does <span class="elsevierStyleSup">99m</span>Tc-tilmanocept, as next generation radiotracer, meet with the requirements for improved sentinel node imaging?" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "275" "paginaFinal" => "280" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "¿El <span class="elsevierStyleSup">99m</span>Tc-tilmanocept, como radiotrazador de próxima generación, cumple con los requisitos para mejorar las imágenes del nodo centinela?" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 2449 "Ancho" => 2500 "Tamanyo" => 434789 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">(Above) Anterior planar static images acquired 10<span class="elsevierStyleHsp" style=""></span>min (on the left) and 2<span class="elsevierStyleHsp" style=""></span>h (on the right) after injection of <span class="elsevierStyleSup">99m</span>Tc-tilmanocept in a patient with a melanoma in the right shoulder showing rapid drainage to two sentinel nodes. Volume rendered SPECT-CT (bottom) shows the sentinel nodes respectively in the right axilla and supraclavicular area. A second echelon node with markedly less uptake accompanies this latter node. At histopathology, isolated tumour cells were found in the supraclavicular SN. The axillary SN resulted tumour negative.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "D.D. Rietbergen, L.M. Pereira Arias-Bouda, J. van der Hage, R.A. Valdés Olmos" "autores" => array:4 [ 0 => array:2 [ "nombre" => "D.D." "apellidos" => "Rietbergen" ] 1 => array:2 [ "nombre" => "L.M." "apellidos" => "Pereira Arias-Bouda" ] 2 => array:2 [ "nombre" => "J." "apellidos" => "van der Hage" ] 3 => array:2 [ "nombre" => "R.A." "apellidos" => "Valdés Olmos" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "es" => array:9 [ "pii" => "S2253654X20301360" "doi" => "10.1016/j.remn.2020.07.004" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2253654X20301360?idApp=UINPBA00004N" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2253808920301191?idApp=UINPBA00004N" "url" => "/22538089/0000004000000005/v1_202108210518/S2253808920301191/v1_202108210518/en/main.assets" ] "en" => array:20 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original Article</span>" "titulo" => "Semiquantitative analysis of interim <span class="elsevierStyleSup">18</span>F-FDG PET is superior in predicting outcome in Hodgkin lymphoma patients compared to visual analysis" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "281" "paginaFinal" => "286" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "T. Ribeiro, A. Marques, G. Ferreira, C. Castro, M. Tavares, A. Espírito-Santo, C. Moreira, J. Mariz" "autores" => array:8 [ 0 => array:4 [ "nombre" => "T." "apellidos" => "Ribeiro" "email" => array:1 [ 0 => "mteresa.gribeiro@hotmail.com" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "A." "apellidos" => "Marques" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "G." "apellidos" => "Ferreira" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 3 => array:3 [ "nombre" => "C." "apellidos" => "Castro" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 4 => array:3 [ "nombre" => "M." "apellidos" => "Tavares" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 5 => array:3 [ "nombre" => "A." "apellidos" => "Espírito-Santo" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 6 => array:3 [ "nombre" => "C." "apellidos" => "Moreira" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 7 => array:3 [ "nombre" => "J." "apellidos" => "Mariz" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] ] "afiliaciones" => array:3 [ 0 => array:3 [ "entidad" => "Onco-Hematology Department, Instituto Português de Oncologia do Porto FG, Street Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Nuclear Medicine Department, Instituto Português de Oncologia do Porto FG, Street Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Epidemiology Department, Instituto Português de Oncologia do Porto FG, Street Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal" "etiqueta" => "c" "identificador" => "aff0015" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "El análisis semicuantitativo del PET provisional <span class="elsevierStyleSup">18</span>F-FDG es superior para predecir el resultado en los pacientes con Linfoma de Hodgkin en comparación con el análisis visual" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 2608 "Ancho" => 3417 "Tamanyo" => 253687 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Progression-free survival curves of HL patients according to PETi scan result as assessed by the five different methods being analyzed (top-left: DeltaSUVmax, top-right: DeltaSUVpeak, bottom-left: DeltaMTV, bottom-right: DeltaTLG).</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Hodgkin lymphoma (HL) has become one of the most curable cancers.<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">1</span></a> Unfortunately, a significant number of patients will suffer from treatment related mortality and morbidity caused by anthracyclines, alkylating agents and radiotherapy.<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">2,3</span></a><span class="elsevierStyleSup">18</span>F-fluorodeoxyglucose positron-emission tomography (PET) has an established role for staging HL and most of non-Hodgkin lymphomas. Early data showed that PET performed after two or three cycles of chemotherapy (interim PET, PETi) is a strong predictor of treatment response in HL, regardless of the baseline prognostic score.<a class="elsevierStyleCrossRefs" href="#bib0145"><span class="elsevierStyleSup">4,5</span></a> PETi emerged, thus, as an important tool to guide response-adapted treatment enabling de-escalation in low-risk patients in order to minimize toxicity (avoiding adjuvant radiation therapy for early HL and abbreviating chemotherapy for advanced HL) and, conversely, escalation in high-risk patients. Several randomized studies in early and advanced HL have been recently published showing a good prognosis for patients who de-escalate therapy after a negative PETi.<a class="elsevierStyleCrossRefs" href="#bib0155"><span class="elsevierStyleSup">6–9</span></a> Two or 4 cycles of ABVD followed by consolidative radiotherapy is still the standard of care for most patients with favourable or unfavourable disease early-stage HL. However, the NCCN provides an alternative of 3 cycles of ABVD and omission of radiotherapy. Both the NCCN and ESMO guidelines recommend the omission of bleomycin after the first 2 cycles of AVBD on most patients with advances-stage HL and a negative PETi.<a class="elsevierStyleCrossRefs" href="#bib0175"><span class="elsevierStyleSup">10,11</span></a> Less robust data suggest improved outcomes with escalation of therapy for patients with positive PETi,<a class="elsevierStyleCrossRefs" href="#bib0160"><span class="elsevierStyleSup">7,8</span></a> but more data is needed to understand long-term toxicity and overall survival.</p><p id="par0010" class="elsevierStylePara elsevierViewall">The Deauville criteria, or 5-point scoring scale (5-PS), is currently the defined standard for reporting PETi. It is a simple, visual interpretation method that compares the residual tumour uptake with the uptake in uninvolved organs within the same image. However, concerns about the interpretation accuracy and reproducibility persist and alternative methods continue to evolve.<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">12</span></a> Semiquantitative methods like metabolic tumour volume (MTV) and maximum standardized uptake value (SUVmax) seem to provide a more uniform and accurate assessment and may be superior to visual analysis in predicting outcome in HL patients.<a class="elsevierStyleCrossRefs" href="#bib0190"><span class="elsevierStyleSup">13,14</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Our aim was to investigate the prognostic value of PETi in adult HL patients, comparing visual with semiquantitative analysis.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Material and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study design and patient selection</span><p id="par0020" class="elsevierStylePara elsevierViewall">We retrospectively analyzed the clinical records of consecutive Hodgkin's lymphoma (HL) adult patients diagnosed according to the WHO criteria, between 2012 and 2016 in the Onco-Hematology Department of Instituto Português de Oncologia – Porto, with a median follow-up of 46.5 months (2.6–66.4). The characteristics of the patients in this preliminary analysis are listed in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>. All histological diagnosis were performed by hemopathologists of our institution.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0025" class="elsevierStylePara elsevierViewall">All histologic subtypes and clinical stages according to Ann Arbor staging were included. Stages IA/B and IIA/B at diagnosis were considered early stages, whereas stages IIIA/B and IVA/B were considered advanced stages. Patients were staged with CT scan or PET scan (PET0), and bone marrow biopsy as per institution protocol at that time. For the present study, only those patients with available PET0 and PETi data were included (total of 58 patients). Fourty one patients were staged with CT scan before referral to our institution and therefore were excluded.</p><p id="par0030" class="elsevierStylePara elsevierViewall">The treatment schedule for each patient followed our Institution treatment protocol (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). Three PET/CT scans were performed: the first exam was conducted at baseline (PET0), the second after two cycles of chemomotherapy (PETi) and the third at the end-of-treatment. Patients with early favourable disease received two cycles of chemotherapy followed by radiotherapy and therefore end-of-treatment PET, in this case was analyzed as PETi.</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0035" class="elsevierStylePara elsevierViewall">The chemotherapy regimen was maintained independent of PETi scan result at that point.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Ethical declaration</span><p id="par0040" class="elsevierStylePara elsevierViewall">The study has been approved by the institutional review board and the need for written informed consent was waived.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">PET scan analysis</span><p id="par0045" class="elsevierStylePara elsevierViewall">PET scan was performed using <span class="elsevierStyleSup">18</span>F-fluorodeoxyglucose (<span class="elsevierStyleSup">18</span>F-FDG) according to our Institution's protocol and acquired using the same equipment for all patients. At the time, analysis was performed by one experienced observer according to Deauville criteria 5-point scale (5-PS): Deauville scores 1–3 were classified as “negative” (in our sample only 5 patients had a Deauville score of 3) and Deauville scores 4 and 5 as “positive” following Lugano 2014 criteria.<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">15</span></a> For this study, maximum standardized uptake value (SUVmax), peak SUV (SUVpeak), metabolic tumour volume (MTV) and total lesion glycolysis index (TLG) were measured as previously described,<a class="elsevierStyleCrossRefs" href="#bib0205"><span class="elsevierStyleSup">16–24</span></a> both in PET0 and PETi. These four measurements were all made retrospectively at our Institution by two observers.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Statistical analysis</span><p id="par0050" class="elsevierStylePara elsevierViewall">After all four parameters were obtained for both PET0 and PETi, the difference between them was calculated as a percentage of the initial value (ΔSUVmax, ΔSUVpeak, ΔMTV and ΔTLG) and cut-off values were determined using receiver-operating curves and Youden index for their best sensitivity and specificity in predicting disease relapse or treatment failure. For 5-PS classification, a positive PETi result consisted of a score of 4 or 5.</p><p id="par0055" class="elsevierStylePara elsevierViewall">Sensitivity, specificity, negative predictive value and positive predictive value for refractory and relapsed disease were also computed for all five parameters according to these previous determinations.</p><p id="par0060" class="elsevierStylePara elsevierViewall">Overall survival was calculated since diagnosis until death or last observation, and progression free survival as the time between the documented complete response during first-line treatment and evidence of relapsed disease. Survival analysis was performed using Kaplan-Meyer curves and log-rank test, p-values lower than 0.05 were considered statistically significant. Statistical analysis was performed using SPSS software version 23.0.</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Semiquantitative analysis</span><p id="par0065" class="elsevierStylePara elsevierViewall">The average values of SUVmax, SUVpeak, MTV and TLG for PET0 and PETi are represented in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>. In general, there was a decrease in the average value of all initial semiquantitative measures under analysis between PET0 and PETi, leading to a difference Δ(PETi<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>PET0) higher than 90% (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>).</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">According to our results, a positive PETi result would consist of a ΔSUVmax lower than 93.5%, ΔSUVpeak lower than 88.4%, ΔMTV lower than 91.9% or ΔTLG lower than 98.3% (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>). ΔSUVpeak had the greatest area under the curve based on the receiver-operating curves (AUC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.741). On the other hand, ΔMTV achieved the best Youden index (Youden index<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.533).</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Comparison of semiquantitative and 5-PS analyses of PETi</span><p id="par0075" class="elsevierStylePara elsevierViewall">Based on our computed cut-off values and the pre-established ones for the Deauville 5-point scoring scale, we classified PETi as positive or negative and subsequently verified how many patients presented with persistent or relapsed disease (<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>).</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><p id="par0080" class="elsevierStylePara elsevierViewall">Of the 58 patients analyzed, 10 presented with persistent or relapsed disease after first-line treatment. There was some similarity between the number of positive or negative PETi scans when semiquantitative parameters were used, but these were strikingly different when Deauville 5-PS was used. According to this visual scale, only two PETi scans would be considered positive (one with persistent or relapsed disease), and nine out of 10 with persistent or relapsed disease would have a negative PETi scan.</p><p id="par0085" class="elsevierStylePara elsevierViewall">Accordingly, semiquantitative analysis obtained a higher sensitivity (70%) compared to the 5-PS (sensitivity of 10%) but lower specificity, in our sample (<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>). The predictive performance for response to first-line therapy was better for semiquantitative analysis than for qualitative visual scale, since it showed a very high negative predictive value compared to the 5-PS. However, the positive predictive value was similar for all five measurements (<a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>).</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Influence of PETi result on patients’ outcome according to semiquantitative and 5-PS analyses</span><p id="par0090" class="elsevierStylePara elsevierViewall">According to Deauville 5-PS, patients with positive PETi had a lower estimated progression free survival (PFS) than patients with negative PETi at 60 months of follow-up (50% vs. 73.8%, respectively), although statistical significance was not reached (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.05).</p><p id="par0095" class="elsevierStylePara elsevierViewall">The semiquantitative approach allowed more accurate identification of patients with a high risk of treatment failure. There is a statistically significant difference between the PFS curves at 60 months of follow-up of patients with positive and negative PETi, according to ΔSUVmax (56.9% vs. 88.0%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), ΔSUVpeak (55.9% vs. 88.1%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), ΔMTV (35.3% vs. 88.7%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), and ΔTLG (42.4% vs. 88.1%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), respectively (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). Patients with a negative PETi according to these measurements showed a greater PFS probability than that obtained by patients with a negative PETi according only to Deauville 5-PS (approximately 88% vs. 73.8%, respectively).</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0100" class="elsevierStylePara elsevierViewall">HL has generally a good prognosis, and accordingly we did not observe any event of death in our sample, which made overall survival analysis impossible.</p></span></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Discussion</span><p id="par0105" class="elsevierStylePara elsevierViewall">PETi as classified by the Deauville criteria 5-point scoring scale (5-PS) has been shown to correlate with HL patients’ outcome,<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">4</span></a> and thus became an interesting tool to guide therapeutic management in these patients.<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">5–8</span></a></p><p id="par0110" class="elsevierStylePara elsevierViewall">Although Deauville 5-PS is to this date the only validated scale for the interpretation of PET scans in HL, it has limitations related to the reproducibility between observers. Therefore, several attempts at finding a more objective and reliable method are being made.</p><p id="par0115" class="elsevierStylePara elsevierViewall">Some studies have demonstrated the superiority of semiquantitative measures in predicting outcome in HL patients compared to the Deauville 5-PS visual scale.<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">14</span></a> In our study, we tried to make this comparison with four different semiquantitative parameters. We obtained a large number (56 out of 58) of negative PETi with visual analysis, but this included nine patients who came to have persistent or relapsed disease. Only two patients had a positive PETi with this method, both with early unfavourable disease treated with chemotherapy (ABVD) plus radiotherapy, but only one with posterior relapse. The small number of positive PETi with this analysis could be related to the sample size, biases related to the retrospective nature of this study, and also a possible contribution of the low sensitivity of the visual analysis. On the other hand, when considering the semiquantitative analysis, only three patients with negative PETi presented with persistent or relapsed disease.</p><p id="par0120" class="elsevierStylePara elsevierViewall">Other retrospective analyses have indicated that early PETi might be a good predictor for treatment failure in patients with advanced HL receiving ABVD chemotherapy.<a class="elsevierStyleCrossRefs" href="#bib0145"><span class="elsevierStyleSup">4,14</span></a> According to our study, semiquantitative analysis obtained a higher sensitivity (70%) and a very high negative predictive value (93–98%) compared to the 5-PS (sensitivity of 10% and negative predictive value 85%) regarding patient response to first-line therapy and early relapsed disease. However, the positive predictive value was similar for all five measurements (39–50%, <a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a>), meaning that either would predict well persistent or relapsed disease in face of a positive PETi result.</p><p id="par0125" class="elsevierStylePara elsevierViewall">When we analyzed PFS curves of patients with negative or positive PETi according to the semiquantitative measurements, at 60 months of follow-up, we observed that patients who did not attain a negative PETi had a significantly lower PFS. This difference, however, was not significant when considering negative or positive PETi result using Deauville 5-PS (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>).</p><p id="par0130" class="elsevierStylePara elsevierViewall">Therefore, our results seem to indicate that semiquantitative analysis of PETi is, in general, more accurate than Deauville 5-PS visual analysis in identifying subsets of patients with significantly different outcomes.</p><p id="par0135" class="elsevierStylePara elsevierViewall">PETi is an important tool for early response evaluation and, in this context, semiquantitative analysis seems to be a good method for early identification of patients who would experience refractory disease with first-line treatment or early relapse, and who could be candidates for alternative therapeutic strategies. On the other hand, given the very high negative predictive value of the semiquantitative measures, a negative PETi result could allow for therapy de-escalation, limiting potential future toxicities in these patients.</p><p id="par0140" class="elsevierStylePara elsevierViewall">The best SUV parameter to be used to assess response to therapy is still unclear, but SUVpeak seems to be the most stable quantitative parameter in predicting event-free survival.<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">25</span></a></p><p id="par0145" class="elsevierStylePara elsevierViewall">Since Deauville 5-PS had the greatest specificity and semiquantitative measures (particularly ΔSUVpeak) the highest negative predictive value, using both methods in association could help improve the clinical value of PETi in the future. We plan to evaluate the prognostic value of the combination of several parameters.</p><p id="par0150" class="elsevierStylePara elsevierViewall">Our study has several limitations, such as the small number of patients analyzed and their heterogeneity in terms of tumour burden at baseline and of treatment regimen they were submitted to, besides the risk of some bias related to its retrospective nature.</p><p id="par0155" class="elsevierStylePara elsevierViewall">The patients’ heterogeneity could be pointed out as a confounding factor to the final results obtained in our analysis; however, it also represents everyday practice more accurately. As methods for PET classification and clinical interpretation would have to be applied (and applicable) ideally to every patient, analysing all types of patients as a whole could strengthen these results and their significance. Although patients included in this study have been treated with different chemotherapy schedules, most of them received ABVD. We cannot determine, based on our data, if the interpretation of PETi by semiquantitative analysis could be influenced by the treatment regimen used.</p><p id="par0160" class="elsevierStylePara elsevierViewall">Results with statistical significance in such a small sample of patients demand for care in their interpretation, since some impact by chance is possible, although the consistency between our findings in all four semiquantitative parameters and their agreement with other works reported could support them. However, more studies are needed to address these questions and guarantee reproducibility of our findings.</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Conclusion</span><p id="par0165" class="elsevierStylePara elsevierViewall">PETi interpretation according to semiquantitative approach appears to discriminate Hodgkin lymphoma patients better than the visual Deauville 5-PS analysis: it could allow better detection of persistent or early relapsed disease, which could otherwise go unnoticed, while a negative PETi result could support de-escalating therapy intensity, limiting related toxicities. Nevertheless, more studies are needed to address these questions and confirm these results.</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Conflict of interest</span><p id="par0170" class="elsevierStylePara elsevierViewall">No potential conflict of interest relevant to this article was reported.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:3 [ "identificador" => "xres1562248" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Purpose" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Material and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Discussion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1408886" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1562247" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Discusión" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1408885" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Material and methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Study design and patient selection" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Ethical declaration" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "PET scan analysis" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Statistical analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0035" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0040" "titulo" => "Semiquantitative analysis" ] 1 => array:2 [ "identificador" => "sec0045" "titulo" => "Comparison of semiquantitative and 5-PS analyses of PETi" ] 2 => array:2 [ "identificador" => "sec0050" "titulo" => "Influence of PETi result on patients’ outcome according to semiquantitative and 5-PS analyses" ] ] ] 7 => array:2 [ "identificador" => "sec0055" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0060" "titulo" => "Conclusion" ] 9 => array:2 [ "identificador" => "sec0065" "titulo" => "Conflict of interest" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2020-03-14" "fechaAceptado" => "2020-06-14" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1408886" "palabras" => array:5 [ 0 => "Hodgkin lymphoma" 1 => "Interim PET" 2 => "Semiquantitative measures" 3 => "Visual analysis" 4 => "Clinical outcome" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1408885" "palabras" => array:5 [ 0 => "Linfoma de Hodgkin" 1 => "PET provisional" 2 => "Medidas semicuantitativas" 3 => "Análisis visual" 4 => "Resultado clínico" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Purpose</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">To investigate the prognostic value of interim PET (PETi) in adult HL patients, comparing visual with semiquantitative analysis.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Material and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Retrospective analysis of Hodgkin's lymphoma (HL) patients diagnosed between 2012 and 2016 in the Onco-hematology Department of Instituto Português de Oncologia – Porto (median follow-up: 46.5 months [2.6–66.4]). Fifty-eight patients with available PET at diagnosis (PET0) and PETi data were included. PETi scans were analyzed according to Deauville 5-point scale (5-PS), and cut-off values for changes in maximum standardized uptake value [SUVmax], peak SUV [SUVpeak], metabolic tumour volume [MTV] and total lesion glycolysis index [TLG] between PETi and PET0 were computed using ROC analysis. Visual and semiquantitative data were compared with each other in the prediction of patient outcomes.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Semiquantitative analysis obtained a higher sensitivity for persistent/relapsed disease compared to the 5-PS (70% vs. 10%, respectively), but lower specificity. It also demonstrated better predictive performance for response to first-line therapy (negative predictive value >92%). The positive predictive value was similar for all five measurements.</p><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">At 60 months of follow-up, there was a significant difference between the progression free survival (PFS) curves of patients with positive and negative PETi according to ΔSUVmax (56.9% vs. 88.0%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), ΔSUVpeak (55.9% vs. 88.1%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), ΔMTV (35.3% vs. 88.7%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), and ΔTLG (42.4% vs. 88.1%, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05). Statistical significance was not reached when considering 5-PS results.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Discussion</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">PETi interpretation according to a semiquantitative approach appears to discriminate HL patients better than the visual 5-PS analysis. This could allow better detection of persistent or early relapsed disease, while a negative PETi result could support de-escalating therapy intensity.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Purpose" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Material and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Discussion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Investigar el valor pronóstico del PET provisional (PETi) en pacientes adultos con HL, comparando el análisis visual con el semicuantitativo.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Material y métodos</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Análisis retrospectivo de pacientes con Linfoma de Hodgkin (LH) diagnosticados entre 2012 y 2016 en el Departamento de Oncología del Instituto Portugués de Oncología - Oporto (mediana de seguimiento: 46,5 meses [2,6–66,4]). Se incluyeron 58 pacientes con PET disponible en el momento del diagnóstico (PET0) y PETi. Las exploraciones de PETi se analizaron de acuerdo con la escala de 5 puntos de Deauville (5-PS), y los valores de corte para los cambios en el valor máximo de captación estandarizada [SUVmax], el SUV máximo [SUVpeak], el volumen tumoral metabólico [MTV] y el índice de glicólisis de la lesión total [TLG] entre el PETi y el PET0 se calcularon mediante el análisis ROC. Los datos visuales y semicuantitativos se compararon entre sí en la predicción de los resultados de los pacientes.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">El análisis semicuantitativo obtuvo una mayor sensibilidad para la enfermedad persistente/recidivante en comparación con el 5-PS (70% vs. 10%, respectivamente), pero una menor especificidad. También demostró un mejor rendimiento predictivo para la respuesta a la terapia de primera línea (valor predictivo negativo >92%). El valor predictivo positivo fue similar en las cinco mediciones.</p><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">A los 60 meses de seguimiento, hubo una diferencia significativa entre las curvas de supervivencia libre de progresión (PFS) de los pacientes con PETi positivo y negativo según SUVmax (56,9% vs. 88,0%, p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,05), ΔSUVpeak (55,9% vs. 88,1%, p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,05), ΔMTV (35,3% vs. 88,7%, p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,05), y ΔTLG (42,4% vs. 88,1%, p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,05). No se alcanzó la significación estadística al considerar los resultados de la 5-PS.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Discusión</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">La interpretación del PETi según un enfoque semicuantitativo parece discriminar mejor a los pacientes con HL que el análisis visual de 5-PS. Esto podría permitir una mejor detección de la enfermedad persistente o de la recaída temprana, mientras que un resultado negativo de PETi podría apoyar la disminución de la intensidad de la terapia.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Discusión" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as: Ribeiro T, Marques A, Ferreira G, Castro C, Tavares M, Espírito-Santo A, et al. El análisis semicuantitativo del PET provisional <span class="elsevierStyleSup">18</span>F-FDG es superior para predecir el resultado en los pacientes con Linfoma de Hodgkin en comparación con el análisis visual. Rev Esp Med Nucl Imagen Mol. 2021;40:281–286.</p>" ] ] "multimedia" => array:6 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 2608 "Ancho" => 3417 "Tamanyo" => 253687 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Progression-free survival curves of HL patients according to PETi scan result as assessed by the five different methods being analyzed (top-left: DeltaSUVmax, top-right: DeltaSUVpeak, bottom-left: DeltaMTV, bottom-right: DeltaTLG).</p>" ] ] 1 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:2 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="4" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Baseline patient characteristics</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">With available PET0 and PETi \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age at diagnosis (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (min.–max.) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33 (18–83) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">30.5 (18–83) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2677037.png" ] ] 1 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">n</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">% \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">n</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">% \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Gender \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Female \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Male \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">54 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">54.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">55.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Performance status \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ECOG 0–1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">97.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">100.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ECOG 2–4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Stage at diagnosis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Early \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">55 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">55.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">62.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Advanced \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Histological subtype \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Nodular lymphocyte-predominant \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Classical \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">87.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">52 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">89.7 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Nodular sclerosis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">74.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">39 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">75.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Lymphocyte rich \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.4 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Lymphocyte depleted \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Mixed cellularity \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>non classified \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Deaths \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2677035.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Baseline characteristics of the 99 Hodgkin Lymphoma patients selected for this study. Only 58 patients had available PET0 and PETi scans to proceed with the study, and their baseline characteristics are listed on the right column. ECOG – Eastern Cooperative Oncology Group scale of performance status. Localized stage at diagnosis refers to Ann Arbour stage IA/B–IIA/B; advanced stage refers to Ann Arbour stage IIIA/B–IVA/B.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">ABVD – doxorubicin (Adriamycin), bleomycin, vinblastine, dacarbazine; BEACOPP – bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, prednisone; CVP/CEB – chlorambucil, vinblastine, procarbazine, cyclophosphamide, etoposide, bleomycin.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="2" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Treatment schedule in first-line treatment</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">First-line treatment \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Number of patients \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Radiotherapy only</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleItalic">Chemotherapy</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">57 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>ABVD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">49 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>BEACOPP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>CVP/CEB \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2677038.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Treatment schedule assigned to the HL patients with available PET0 and PETi. Only one patient didn’t receive chemotherapy. Thirty-six patients received combined treatment with chemotherapy and radiotherapy.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="5" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Results of PET0 and PETi semiquantitative measurements</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">SUVmax \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">SUVpeak \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">MTV \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">TLG \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PET0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.01 [2.28–19.99] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8.24 [1.52–17.44] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">171.21<span class="elsevierStyleHsp" style=""></span>cm<span class="elsevierStyleSup">3</span> [3.1–992.1] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">847.76<span class="elsevierStyleHsp" style=""></span>cm<span class="elsevierStyleSup">3</span> [3.96–4290.94] \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PETi \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.93 [0–11.18] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.70 [0–7.59] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.38<span class="elsevierStyleHsp" style=""></span>cm<span class="elsevierStyleSup">3</span> [0–76.11] \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.18<span class="elsevierStyleHsp" style=""></span>cm<span class="elsevierStyleSup">3</span> [0–91.5] \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Δ(PETi<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>PET0)% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">90.35% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">91.67% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">93.06% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">97.94% \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2677039.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Average values of SUVmax, SUVpeak, MTV and TLG of staging PET (PET0) and interim PET (PETi). Minimum and maximum values are represented between square brackets for each parameter. The average difference in percentage between PETi and PET0 (Δ(PETi<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>PET0)%) was calculated for each parameter and is displayed in the bottom line.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at4" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="5" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Distribution of PETi results and clinical outcomes</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="2" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Positive PETi</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="2" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Negative PETi</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">RR disease \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">RR disease \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5-PS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">56 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ΔSUVmax \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">40 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ΔSUVpeak \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ΔMTV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ΔTLG \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2677036.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">Number of patients with positive or negative PETi according to the 5 parameters in analysis and respective outcome. PETi: interim PET; RR: refractory or relapsed disease.</p>" ] ] 5 => array:8 [ "identificador" => "tbl0025" "etiqueta" => "Table 5" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at5" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">CI 95% – 95% confidence interval.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="6" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Performance of each parameter under analysis in predicting outcome</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">5-PS \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">ΔSUVmax \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">ΔSUVpeak \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">ΔMTV \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col">ΔTLG \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">1,2,3 vs.4,5 \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">≤93% vs. >93% \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">≤88% vs. >88% \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">≤91.9% vs. >91.9% \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">≤98.3% vs. >98.3% \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sensitivity \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (0.25–44.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (34.8–93.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (34.8–93.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (34.8–93.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (34.8–93.3) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Specificity \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">98% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">77% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">79% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">83% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">81.3% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (89.5–99.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (62.7–88.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (65.0–89.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (69.8–92.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (67.4–91.1) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Negative predictive value \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">85% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">93% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">98% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">93% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">92.9% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (81.3–87.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (82.5–97.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (82.9–97.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (83.7–97.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (83.3–97.1) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Positive predictive value \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">39% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">46.7% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">43.8% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (6.37–93.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (24.8–55.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (58.3–86.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (29.2–65.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CI 95% (27.6–61.4) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2677040.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">Sensitivity, specificity, negative predictive value and positive predictive value for persistent or relapsed disease after first-line treatment for all five parameters in this study.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:25 [ 0 => array:3 [ "identificador" => "bib0130" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Eight cycles of ABVD versus four cycles of BEACOPPescalated plus four cycles of BEACOPPbaseline in stage III to IV, international prognostic score >/=3, high-risk Hodgkin lymphoma: first results of the phase III EORTC 20012 intergroup trial" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "P. 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