Original article
APACHE II score for critically ill patients with a solid tumor: A reclassification study
Escala APACHE II para pacientes críticos con cáncer sólido. Estudio de reclasificación
F.D. Martos-Beníteza,
, I. Cordero-Escobarb, A. Soto-Garcíac, I. Betancourt-Plazad, I. González-Martínezd
Corresponding author
a Unidad de Cuidados Intensivos 8B, Hospital “Hermanos Ameijeiras”, La Habana, Cuba
b Departamento de Anestesiología, Hospital “Hermanos Ameijeiras”, La Habana, Cuba
c Unidad de Cuidados Intensivos Oncológicos, Instituto de Oncología y Radiobiología, La Habana, Cuba
d Unidad de Cuidados Intensivos, Hospital Docente “Dr. Miguel Enríquez”, La Habana, Cuba
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"apellidos" => "Betancourt-Plaza" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] 4 => array:3 [ "nombre" => "I." "apellidos" => "González-Martínez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Unidad de Cuidados Intensivos 8B, Hospital “Hermanos Ameijeiras”, La Habana, Cuba" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Departamento de Anestesiología, Hospital “Hermanos Ameijeiras”, La Habana, Cuba" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Unidad de Cuidados Intensivos Oncológicos, Instituto de Oncología y Radiobiología, La Habana, Cuba" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Unidad de Cuidados Intensivos, Hospital Docente “Dr. Miguel Enríquez”, La Habana, Cuba" "etiqueta" => "d" "identificador" => "aff0020" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Escala APACHE II para pacientes críticos con cáncer sólido. Estudio de reclasificación" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1649 "Ancho" => 2158 "Tamanyo" => 182647 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">ROC curve for selected model (APACHE II<span class="elsevierStyleInf">CCP</span>) in multivariate logistic regression analysis (AROC 0.91; 95% CI 0.87–0.94; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001), and ROC curve for general APACHE II (AROC 0.62; 95% CI 0.54–0.70; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.002). Scored area depicts the increase in AROC. AROC, area under receiver-operating characteristic curve; APACHE, Acute Physiology and Chronic Health Evaluation; APACHE II<span class="elsevierStyleInf">CCP</span>, APACHE II for critically ill patients with a solid tumor; CI, confidence interval; ROC, receiver-operating characteristic.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Prognosis in cancer patients admitted to the intensive care unit (ICU) has improved in recent years<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">1</span></a>; however, mortality rates remain high.<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">2–4</span></a> Sepsis, acute respiratory failure, cancer-related complications, and chemotherapy-induced adverse events are the main factors associated with higher mortality in this subpopulation.<a class="elsevierStyleCrossRefs" href="#bib0145"><span class="elsevierStyleSup">1,5</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Mortality prediction is crucial for the management of critically ill cancer patients. Predictive models used in critical care medicine were designed for general populations and are therefore difficult to use in subpopulations. Validity studies in critically ill patients with cancer are insufficient; additionally, the findings of existing studies cannot be generalised because of their limitations, such as the diversity of models evaluated, retrospective design, small sample sizes, low mortality rates, and bias arising from different standards of care in participating ICUs.<a class="elsevierStyleCrossRefs" href="#bib0170"><span class="elsevierStyleSup">6,7</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Groeger et al.<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">8</span></a> developed a specific prognostic model for critically ill patients with cancer, the Cancer Mortality Model (CMM). However, a recent study demonstrated an inferior performance compared with general prognostic models.<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">6</span></a> Thus, a specific prognostic model does not seem to resolve the problem of mortality risk prediction in these patients. However, a general model adapted to critically ill cancer patients using a reclassification analysis could be an attractive alternative. The aim of this study has been to improve the accuracy of the Acute Physiology and Chronic Health Evaluation (APACHE) II model for predicting hospital mortality in critically ill patients with solid tumors.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Materials and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Design and setting</span><p id="par0020" class="elsevierStylePara elsevierViewall">This was a prospective cohort study carried out in the oncological ICU of the Institute of Oncology and Radiobiology (IOR) from January 2014 to December 2015. This is a 220-bed, university-affiliated, tertiary care referral centre for cancer patients in Havana, Cuba. The ICU has 12 beds and provides care for about 500 medical and surgical cancer patients per year. The study was conducted in accordance with the Declaration of Helsinki and approved by the Scientific Council and the Research Ethics Committee of the IOR. Written informed consent was obtained from all individual participants.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Participants</span><p id="par0025" class="elsevierStylePara elsevierViewall">A total of 1029 patients were consecutively admitted to the ICU over the study period. Of these, 992 patients with a solid tumor were included, irrespective of histology, tumor location, clinical stage, or reason for ICU admission. Patients admitted to the ICU for <24<span class="elsevierStyleHsp" style=""></span>h were excluded (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). Two subgroups of patients were not analysed in order to reduce the risk of selection bias: (1) patients who died within 24<span class="elsevierStyleHsp" style=""></span>h of ICU admission; and (2) patients with a lower risk of death admitted to the ICU for 24-h postoperative surveillance according to institutional protocols. In the case of patients admitted more than once to the ICU during the same hospital stay, only the first data on ICU admission were collected. Patients were included in the study if both the oncologist and the ICU physician generally agreed that they had a chance of recovering from the acute problem. Conversely, patients with no further oncology-specific treatment options were offered end-of-life care on the referring ward and not transferred to the ICU.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Data collection and outcomes</span><p id="par0030" class="elsevierStylePara elsevierViewall">The following demographic and clinical data were obtained within 24<span class="elsevierStyleHsp" style=""></span>h of ICU admission: age, sex, age-adjusted Charlson comorbidity index (ACCI) score with the exclusion of malignancy, primary tumor location, clinical stage of cancer, history of anticancer therapy, origin of the patient (hospital ward or emergency department), type of admission (surgical or non-surgical), reason for admission (malignancy-related or non-malignancy-related), APACHE II score, sepsis, chemotherapy-induced adverse event as the reason for ICU admission, and requirement of invasive mechanical ventilation (MV).</p><p id="par0035" class="elsevierStylePara elsevierViewall">The reason for admission was defined as “malignancy-related” if the clinical reason for ICU admission was directly related with the tumor tissue (e.g., primary surgical intervention [tumor-resection or tumor-occlusion/perforation], tumor infection/haemorrhage, tumor lysis syndrome, paraneoplastic syndrome, infiltrative or metastatic organ dysfunction). Otherwise, it was categorised as “non-malignancy-related” (e.g., infection/haemorrhage of non-tumor-tissue, surgical re-intervention due to any complication of primary surgery, anticancer therapy-related adverse event).<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">9</span></a></p><p id="par0040" class="elsevierStylePara elsevierViewall">The primary outcome of interest was hospital mortality. We also recorded ICU mortality, length of ICU stay, unplanned ICU re-admission, and length of hospital stay.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Statistical analysis</span><p id="par0045" class="elsevierStylePara elsevierViewall">Categorical variables are shown as counts and percentages, and numerical variables as median and interquartile range (IQR). For categorical variables, Pearson's chi-squared test (<span class="elsevierStyleItalic">χ</span><span class="elsevierStyleSup">2</span>) was used to determine the differences between groups. Because of lack of normality, the Mann–Whitney <span class="elsevierStyleItalic">U</span>-test was used for numerical variables.</p><p id="par0050" class="elsevierStylePara elsevierViewall">Multivariate logistic regression (MLR) analysis was used to identify risk factors associated with hospital mortality. Because of lack of normality, the APACHE II score was transformed by natural logarithm (Ln). Nine parsimony models were tested, in which only explanatory variables yielding <span class="elsevierStyleItalic">p</span>-values ≤0.25 in the univariate analysis were added to the model containing the general APACHE II score. The model was checked for possible interaction terms. Models were developed using backward stepwise (likelihood ratio) testing (<span class="elsevierStyleItalic">p</span>-value to enter: 0.10; <span class="elsevierStyleItalic">p</span>-value to remove: 0.15). The model with the lowest Bayesian informative criterion (BIC) was selected as the final model (named APACHE II for critically ill patients with a solid tumor [APACHE II<span class="elsevierStyleInf">CCP</span>]). The Hosmer–Lemeshow goodness-of-fit test <span class="elsevierStyleItalic">C</span> statistic was used to evaluate agreement between the observed and expected number of survivors and non-survivors across all the mortality probability strata (calibration). Discrimination was evaluated by calculating the area under the receiver-operating characteristic curve (AROC); an AROC of 1.0 denotes perfect discrimination, while a value close to 0.50 indicates no apparent accuracy.</p><p id="par0055" class="elsevierStylePara elsevierViewall">The improvement in predicting hospital mortality with APACHE II<span class="elsevierStyleInf">CCP</span> was assessed by the increase in AROC (IAROC), integrated discrimination improvement (IDI), net reclassification improvement (NRI), and quantitative NRI (qNRI). IDI, NRI, and qNRI are applicable to situations in which new predictors are added to a known model.<a class="elsevierStyleCrossRefs" href="#bib0190"><span class="elsevierStyleSup">10,11</span></a> In this study, typical variables of critically ill cancer patients were added to the general APACHE II model.</p><p id="par0060" class="elsevierStylePara elsevierViewall">IAROC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>AROC<span class="elsevierStyleInf">new</span> – AROC<span class="elsevierStyleInf">old</span>. AROC<span class="elsevierStyleInf">new</span> is the AROC in APACHE II<span class="elsevierStyleInf">CCP</span>, and AROC<span class="elsevierStyleInf">old</span> is the AROC in the general APACHE II model. IAROC was used to quantify improvement in discrimination.</p><p id="par0065" class="elsevierStylePara elsevierViewall">IDI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>(<span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">new</span>,<span class="elsevierStyleInf">event</span> – <span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">old</span>,<span class="elsevierStyleInf">event</span>) – (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">new</span>,<span class="elsevierStyleInf">non-event</span> – <span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">old</span>,<span class="elsevierStyleInf">non-event</span>). <span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">new</span>,<span class="elsevierStyleInf">event</span> and <span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">old</span>,<span class="elsevierStyleInf">event</span> are the mean estimated probability of hospital death by APACHE II<span class="elsevierStyleInf">CCP</span> and general APACHE II scores in non-survivors, respectively; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">new</span>,<span class="elsevierStyleInf">non-event</span> and <span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">old</span>,<span class="elsevierStyleInf">non-event</span> are the mean estimated probability of hospital survival by APACHE II<span class="elsevierStyleInf">CCP</span> and general APACHE II scores in survivors, respectively. IDI was used to quantify increases in separation of events and non-events.</p><p id="par0070" class="elsevierStylePara elsevierViewall">NRI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>(<span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">moving</span><span class="elsevierStyleInf">up</span>,<span class="elsevierStyleInf">event</span> – <span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">moving</span><span class="elsevierStyleInf">down</span>,<span class="elsevierStyleInf">event</span>)<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>(<span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">moving</span><span class="elsevierStyleInf">down</span>,<span class="elsevierStyleInf">non-event</span> – <span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">moving</span><span class="elsevierStyleInf">up</span>,<span class="elsevierStyleInf">non-event</span>). Any <span class="elsevierStyleItalic">upward</span> movement across classes for non-surviving patients implies improvement, whereas any <span class="elsevierStyleItalic">downward</span> movement across classes indicates worse reclassification. The NRI is the sum difference of the proportion of individuals moved up (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">moving</span><span class="elsevierStyleInf">up</span>,<span class="elsevierStyleInf">event</span>) minus proportion of those who moved down (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">moving</span><span class="elsevierStyleInf">down</span>,<span class="elsevierStyleInf">event</span>) among event subjects, and the proportion of individuals moved down (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">moving</span><span class="elsevierStyleInf">down</span>,<span class="elsevierStyleInf">nonevent</span>) minus the proportion of those who moved up (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">moving</span><span class="elsevierStyleInf">up</span>,<span class="elsevierStyleInf">non-event</span>) among non-event subjects. The categories of hospital mortality risk used for NRI calculation were high risk (>20%), and low risk (≤20%). NRI was used to quantify the number of correct reclassifications obtained using the APACHE II<span class="elsevierStyleInf">CCP</span> model.</p><p id="par0075" class="elsevierStylePara elsevierViewall">The qNRI considers whether each individual moves up (to higher) or down in individual calculated risk of hospital death with the APACHE II<span class="elsevierStyleInf">CCP</span> model. The minimum qNRI is 0% (calculated risks for all subjects with events are decreased, and all subjects without events are increased); conversely, the maximum qNRI is 200% (calculated risks for all subjects with events are increased, and all subjects without events are decreased).</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Development of the scoring system and risk calculator</span><p id="par0080" class="elsevierStylePara elsevierViewall">The simplified scoring system was developed in five steps, based on converting the regression coefficient for each predictor to integers: (1) estimate the regression coefficients (<span class="elsevierStyleItalic">β</span>) of the multivariable model; (2) organise the risk factors into categories and determine the baseline category and reference values for each variable; (3) determine how far each category is from the reference category in regression units; (4) set the base constant; and (5) determine the number of points for each category of each variable.<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">12</span></a></p><p id="par0085" class="elsevierStylePara elsevierViewall">Once the model was developed, it was used to build the risk calculator. The estimated probability of hospital death can be obtained directly using the logistic regression model. The MLR model is as follows:</p><p id="par0090" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">L</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">β</span><span class="elsevierStyleInf">0</span><span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">β</span><span class="elsevierStyleInf">1</span><span class="elsevierStyleItalic">X</span><span class="elsevierStyleInf">1</span><span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>⋯<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">β</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">k</span></span><span class="elsevierStyleItalic">X</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">k</span></span></p><p id="par0095" class="elsevierStylePara elsevierViewall">where <span class="elsevierStyleItalic">L</span> is the logit function, <span class="elsevierStyleItalic">β</span><span class="elsevierStyleInf">0</span> is the intercept in the model, <span class="elsevierStyleItalic">β</span><span class="elsevierStyleInf">1</span>, …, <span class="elsevierStyleItalic">β</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">k</span></span> is the regression coefficient (=log odds ratio) for each predictor (<span class="elsevierStyleItalic">X</span><span class="elsevierStyleInf">1</span>, …, <span class="elsevierStyleItalic">X</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">k</span></span>). The estimated probability percentage of hospital death for a patient is then computed using the following formula<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">13</span></a>:<elsevierMultimedia ident="eq0005"></elsevierMultimedia></p><p id="par0100" class="elsevierStylePara elsevierViewall">Statistical tests with a two-tailed <span class="elsevierStyleItalic">p</span>-value ≤0.05 were considered significant. Data were analysed using IBM<span class="elsevierStyleSup">®</span> SPSS<span class="elsevierStyleSup">®</span> Statistics 23.0 (IBM, Armonk, NY, USA).</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Results</span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Patient characteristics</span><p id="par0105" class="elsevierStylePara elsevierViewall">The median age in 522 study patients was 60.5 years (IQR 51.0–69.0 years). The median ACCI score was 3.0 (IQR 2.0–5.0 points). Gastrointestinal tract (35.2%), thorax (25.3%), and gynaecological tract (10.0%) were the most common primary tumor locations. Advanced cancer was observed in 53.3% of patients (stage III 29.7% and stage IV 23.6%). Most patients (90.2%) were admitted to the ICU from hospital wards, and most were surgical patients (elective surgical patients 74.7% vs. emergency surgical patients 4.4% vs. non-surgical patients 20.9%). Most admissions were malignancy-related (82.2%). Sepsis and chemotherapy-induced adverse events accounted for 7.1 and 5.0%, respectively (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0110" class="elsevierStylePara elsevierViewall">Invasive mechanical ventilation was required in 15.5% of patients; the median ventilation time was 9.0 days (IQR 6.0–15.0 days) (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>). The median length of ICU stay and length of hospital stay was 3.0 days (IQR 2.0–4.0 days) and 9.0 days (IQR 6.0–14.0 days), respectively. Unplanned ICU re-admission was required in 4.4% of patients.</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Mortality and predictive variables</span><p id="par0115" class="elsevierStylePara elsevierViewall">The ICU and hospital mortality rates were 10.2% (53 patients) and 13.0% (68 patients), respectively. In the univariate analysis, ACCI score (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.001), primary tumor location (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.001), clinical stage of cancer (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001), origin of the patient (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001), type of admission (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001), reason for admission (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001), general APACHE II score (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.002), sepsis (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001), chemotherapy-induced adverse event (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001), and MV (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001) were factors related with hospital mortality (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Performance of general APACHE II</span><p id="par0120" class="elsevierStylePara elsevierViewall">A higher general APACHE II score was associated with an increased risk of hospital death (OR 1.71; 95% CI 1.09–1.26; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001). However, calibration was poor (Hosmer–Lemeshow <span class="elsevierStyleItalic">X</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>25.75; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.001), and discrimination was moderate (AROC 0.62; 95% CI 0.54–0.70; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.002) (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>).</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">APACHE II for critically ill patients with a solid tumor</span><p id="par0125" class="elsevierStylePara elsevierViewall">All MLR models tested showed adequate calibration (<span class="elsevierStyleItalic">p</span>-value >0.05 in the Hosmer–Lemeshow test for all models) and good discrimination (AROC<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>0.88 for all models) (<a class="elsevierStyleCrossRef" href="#sec0090">anexo 1Available in on line Supplementary material</a>). The chosen model (APACHE II<span class="elsevierStyleInf">CCP</span>) had a BIC-value of 267. This model presented appropriate calibration (Hosmer–Lemeshow <span class="elsevierStyleItalic">X</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">2</span></span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>9.97; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.267) and very good discrimination (AROC 0.91; 95% CI 0.87–0.94; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001). The result of the MLR analysis for APACHE II<span class="elsevierStyleInf">CCP</span> is shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> and <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>. The scoring system is presented in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>.</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Evaluation of improvement in predicting mortality with APACHE II<span class="elsevierStyleInf">CCP</span></span><p id="par0130" class="elsevierStylePara elsevierViewall">The IAROC with APACHE II<span class="elsevierStyleInf">CCP</span> was 0.29 (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>), which indicates that discrimination of this new predictive model is better than that for the general APACHE II model. Discrimination capacity improved by 30% (IDI 0.30; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001) in APACHE II<span class="elsevierStyleInf">CCP</span> compared with the general APACHE II system. The qNRI was 64.7% (95% CI 40.9–88.5%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001) for non-surviving patients, while the qNRI was 69.6% (95% CI 60.4–78.8%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001) for surviving patients. The total qNRI was 134.3% (95% CI 108.8–159.8%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001).</p><p id="par0135" class="elsevierStylePara elsevierViewall">Of 68 non-surviving patients, 35 (51.5%) were classified in a higher category of mortality risk and 2 (2.9%) were classified in a lower category of risk with APACHE II<span class="elsevierStyleInf">CCP</span>. On the other hand, of 454 surviving patients, 42 (9.3%) were classified in a higher category of mortality risk and 10 (2.2%) were classified in a lower category of risk with APACHE II<span class="elsevierStyleInf">CCP</span>.</p><p id="par0140" class="elsevierStylePara elsevierViewall">The NRI was 48.5% (95% CI 31.0–66.1%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001) for non-surviving patients, and −7.1% (95% CI −10.2 to −3.9%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001) for surviving patients. The total NRI was 41.5% (95% CI 23.7–59.3%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001); that is, compared with the general APACHE II model, 41.5% of patients were reclassified in a new category of mortality risk with APACHE II<span class="elsevierStyleInf">CCP</span>.</p></span></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Discussion</span><p id="par0145" class="elsevierStylePara elsevierViewall">This reclassification study showed that APACHE II<span class="elsevierStyleInf">CCP</span> was superior to the general APACHE II model for predicting mortality in critically ill patients with a solid tumor. Performance was improved, and 40% of patients were reclassified in a different mortality risk category.</p><p id="par0150" class="elsevierStylePara elsevierViewall">The APACHE II<span class="elsevierStyleInf">CCP</span> model was developed using novel methods of reclassification involving modern, more sensitive statistical techniques to reclassify and improve existing clinical models using new predictors. Pencina et al. recently showed that qNRI depends on effect size (e.g. OR) and correlation of new variables (in this case “invasive mechanical ventilation”, “clinical stage of cancer”, and “nature of admission”) with old predictors (in this case “general APACHE II”) in the model.<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">14</span></a> A high qNRI was observed with APACHE II<span class="elsevierStyleInf">CCP</span>, which confirms its good predictive capacity.</p><p id="par0155" class="elsevierStylePara elsevierViewall">General predictive models in critically ill patients with cancer have shown good results, but they are insufficient. Soares et al. observed that discrimination was superior for both the Simplified Acute Physiology Score (SAPS) 2 (AROC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.84) and SAPS 3 (AROC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.84) compared to the CMM (AROC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.79) and Mortality Probability Model (MPM) III (AROC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.71); however, calibration was better using the CMM and the SAPS 3 weighted for South American countries.<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">6</span></a> Nevertheless, this study presented several limitations, such as small sample size for a multicentre study, and different characteristics and standards of care among participating ICUs; furthermore, APACHE II-IV models were not analysed.</p><p id="par0160" class="elsevierStylePara elsevierViewall">Recently, Xing et al. found an AROC of 0.95, 0.86, and 0.87 for SAPS 3, APACHE II, and APACHE IV, respectively. Furthermore, the best calibration was observed for APACHE II.<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">7</span></a> However, this was a single centre study with a small number of patients with metastatic tumors. In addition, the overall hospital mortality rate was very low (only 4.5%), which might have an impact on the performance of all prognostic models.</p><p id="par0165" class="elsevierStylePara elsevierViewall">The APACHE II<span class="elsevierStyleInf">CCP</span> combines a general predictive model (APACHE II) with variables typical of critically ill cancer patients. It comprises two components and four variables: Component (1) general predictive model: the APACHE II; component (2) 1 organ support variable: invasive mechanical ventilation; and two cancer-specific variables: clinical stage of cancer and nature of admission.</p><p id="par0170" class="elsevierStylePara elsevierViewall">The general APACHE II contains variables evaluating acute pathophysiological imbalance and chronic health evaluation. This model was selected for our study because it is widely used not only in Cuba, but also in many other countries<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">15–21</span></a>; furthermore, it is the prognostic model routinely used in our ICU.</p><p id="par0175" class="elsevierStylePara elsevierViewall">Mechanical ventilation is a life-support strategy commonly used in the management of critically ill cancer patients with acute respiratory failure.<a class="elsevierStyleCrossRefs" href="#bib0250"><span class="elsevierStyleSup">22–25</span></a> However, it is a risk factor independently associated with higher mortality in this population,<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">2,4,5,25</span></a> probably as a consequence of new-onset pulmonary disorders such as ventilator-induced lung injury<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">26</span></a> and ventilator-associated pneumonia.<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">27</span></a> The hospital mortality rate among critically ill ventilated patients with cancer exceeds 65%.<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">22</span></a> In addition, the mortality rate is twice as high in critically ill ventilated patients with cancer compared to non-ventilated cancer patients.<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">2</span></a> This is why mortality prediction is improved when MV is included as an explicative variable in APACHE II<span class="elsevierStyleInf">CCP</span>.</p><p id="par0180" class="elsevierStylePara elsevierViewall">The reason for admission was defined as previously described.<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">9</span></a> This definition should be used in future studies that are compared with our results. Recently, Martos-Benítez et al. showed that non-malignancy-related admission was a powerful risk factor independently associated with hospital mortality in cancer patients admitted to the ICU (OR 5.80; 95% CI 3.26–10.32; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001).<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">9</span></a></p><p id="par0185" class="elsevierStylePara elsevierViewall">Several studies suggest that advanced cancer, metastasis, or progression are associated with a higher mortality rates in cancer patients admitted to ICU.<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">2,3,5,23,24,28</span></a> Consequently, it is not surprising that APACHE II<span class="elsevierStyleInf">CCP</span> performed better, since the clinical stage of cancer was added to the model.</p><p id="par0190" class="elsevierStylePara elsevierViewall">The strengths of this study include its prospective design. However, it has several shortcomings. First, it was a single centre study restricted to critically ill patients with a solid tumor. Therefore, the results cannot be generalised to patients without cancer. Second, haematological cancer patients were poorly represented, and there were no patients with leukaemia. However, patients with a haematological malignancy have also been underrepresented in previous studies where a heterogeneous cohort of critically ill cancer patients was analysed.<a class="elsevierStyleCrossRefs" href="#bib0170"><span class="elsevierStyleSup">6,7</span></a> Finally, more than 75% of patients were admitted to the ICU for postoperative care. Therefore, the results of this study were similar to those of general surgical ICU studies.<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">17</span></a></p><p id="par0195" class="elsevierStylePara elsevierViewall">In conclusion, the performance of APACHE II<span class="elsevierStyleInf">CCP</span> was superior to the general APACHE II model, both in terms of discrimination and calibration. This new model for critically ill cancer patients is an effective predictive tool that gives an accurate prognostic evaluation in the ICU setting. The present results need to be validated in a large multicentre study.</p></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Conflicts of interest</span><p id="par0210" class="elsevierStylePara elsevierViewall">All authors declare no conflict of interests.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:10 [ 0 => array:3 [ "identificador" => "xres1092844" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Materials and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1035702" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1092845" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1035701" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Materials and methods" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Design and setting" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Participants" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Data collection and outcomes" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Statistical analysis" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Development of the scoring system and risk calculator" ] ] ] 6 => array:3 [ "identificador" => "sec0040" "titulo" => "Results" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0045" "titulo" => "Patient characteristics" ] 1 => array:2 [ "identificador" => "sec0050" "titulo" => "Mortality and predictive variables" ] 2 => array:2 [ "identificador" => "sec0055" "titulo" => "Performance of general APACHE II" ] 3 => array:2 [ "identificador" => "sec0060" "titulo" => "APACHE II for critically ill patients with a solid tumor" ] 4 => array:2 [ "identificador" => "sec0065" "titulo" => "Evaluation of improvement in predicting mortality with APACHE II" ] ] ] 7 => array:2 [ "identificador" => "sec0070" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0085" "titulo" => "Conflicts of interest" ] 9 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2018-01-04" "fechaAceptado" => "2018-04-18" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1035702" "palabras" => array:5 [ 0 => "APACHE" 1 => "Cancer" 2 => "Critically ill patient" 3 => "Mortality" 4 => "Prognostic score" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1035701" "palabras" => array:5 [ 0 => "APACHE" 1 => "Cáncer" 2 => "Escala pronóstica" 3 => "Mortalidad" 4 => "Paciente críticamente enfermo" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">To improve the accuracy of the Acute Physiology and Chronic Health Evaluation (APACHE) II model for predicting hospital mortality in critically ill cancer patients.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Materials and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">This was a prospective cohort study of 522 patients admitted to ICU with a solid tumor. We developed the “APACHE II score for critically ill patients with a solid tumor” (APACHE II<span class="elsevierStyleInf">CCP</span> score), in which typical variables of critically ill cancer patients were added to general APACHE II score. Calibration and discrimination were evaluated by Hosmer–Lemeshow test (H–L) and area under receiver operating characteristic curve (AROC), respectively. The improvement in predicting hospital mortality with the new model was assessed using a reclassification analysis by integrated discrimination improvement (IDI), net reclassification improvement (NRI; cut-off point of 20% in risk of death) and quantitative NRI (qNRI).</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The hospital mortality rate was 13%. Discrimination was superior for APACHE II<span class="elsevierStyleInf">CCP</span> score (AROC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.91 [95% CI 0.87–0.94; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001]) compared to general APACHE II score (AROC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.62 [95% CI 0.54–0.70; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.002]). Calibration was better using APACHE II<span class="elsevierStyleInf">CCP</span> score (H–L; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.267 vs. <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.001). In reclassification analysis, an improved mortality prediction was observed with APACHE II<span class="elsevierStyleInf">CCP</span> score (IDI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.2994 [<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001]; total qNRI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>134.3% [95% CI 108.8–159.8%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001]; total NRI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>41.5% [95% CI 23.7–59.3%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001]).</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">The performance of APACHE II<span class="elsevierStyleInf">CCP</span> score was superior to that observed for general APACHE II score in predicting mortality in critically ill patients with a solid tumor. Other studies validating this new predictive model are required.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Materials and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Mejorar el rendimiento de la escala Acute Physiology and Chronic Health Evaluation (APACHE) II para la predicción de muerte hospitalaria en pacientes críticos con cáncer.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Materiales y métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Estudio prospectivo de 522 pacientes con cáncer sólido admitidos en UCI. Se creó la «escala APACHE II para pacientes con cáncer sólido» (escala APACHE II<span class="elsevierStyleInf">PCC</span>); se adicionaron variables típicas del paciente oncológico crítico a la escala APACHE II general. Se evaluó la calibración (prueba de Hosmer–Lemeshow [H–L]) y discriminación (área bajo la curva de las características operativas del receptor [ACOR]). Se utilizó la mejora en la discriminación integrada (IDI), mejora neta en la reclasificación (NRI; 20% como valour de corte en el riesgo de muerte) y NRI cuantitativo (cNRI) para evaluar la mejora en la predicción de muerte hospitalaria con el nuevo modelo.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">La mortalidad hospitalaria fue del 13%. La discriminación fue superior con la escala APACHE II<span class="elsevierStyleInf">CCP</span> (ACOR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,91 [IC del 95% 0,87–0,94; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,0001]) comparado con la escala APACHE II general (ACOR<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,62 [IC del 95% 0,54–0,70; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,002]). La calibración fue mejor con la escala APACHE II<span class="elsevierStyleInf">CCP</span> (H-L <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,267 vs. <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,001). En el análisis de reclasificación se observó una mejora en la predicción de muerte con la escala APACHE II<span class="elsevierStyleInf">CCP</span> (IDI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,2994 [<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,0001]; cNRI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>134,3% [IC del 95% 108,8–159,8%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,0001]; NRI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>41,5% [IC del 95% 23,7–59,3%; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,0001]).</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">La escala APACHE II<span class="elsevierStyleInf">CCP</span> fue superior a la escala APACHE II general en la predicción de muerte en pacientes críticos con cáncer sólido. Se requieren otros estudios que validen este nuevo modelo predictivo.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:2 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0015">Please cite this article as: Martos-Benítez FD, Cordero-Escobar I, Soto-García A, Betancourt-Plaza I, González-Martínez I. Escala APACHE II para pacientes críticos con cáncer sólido. Estudio de reclasificación. Rev Esp Anestesiol Reanimación. 2018;65:447–455.</p>" ] 1 => array:2 [ "etiqueta" => "☆☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0025">This article is part of the Anaesthesiology and Resuscitation Continuing Medical Education Program. An evaluation of the questions on this article can be made through the Internet by accessing the Education Section of the following web page: <a class="elsevierStyleInterRef" target="_blank" id="intr0005" href="https://www.elsevier.es/redar">https://www.elsevier.es/redar</a></p>" ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<p id="par0220" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="upi0005"></elsevierMultimedia></p>" "etiqueta" => "Appendix A" "titulo" => "Supplementary data" "identificador" => "sec0095" ] ] ] ] "multimedia" => array:7 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1947 "Ancho" => 2175 "Tamanyo" => 161242 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Flow diagram of participants. ICU, intensive care unit.</p>" ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1649 "Ancho" => 2158 "Tamanyo" => 182647 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">ROC curve for selected model (APACHE II<span class="elsevierStyleInf">CCP</span>) in multivariate logistic regression analysis (AROC 0.91; 95% CI 0.87–0.94; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.0001), and ROC curve for general APACHE II (AROC 0.62; 95% CI 0.54–0.70; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.002). Scored area depicts the increase in AROC. AROC, area under receiver-operating characteristic curve; APACHE, Acute Physiology and Chronic Health Evaluation; APACHE II<span class="elsevierStyleInf">CCP</span>, APACHE II for critically ill patients with a solid tumor; CI, confidence interval; ROC, receiver-operating characteristic.</p>" ] ] 2 => 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:3 [ "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">ACCI, Age-Adjusted Charlson Comorbidity Index; APACHE, Acute Physiology and Chronic Health Evaluation; ICU, intensive care unit; IQR, interquartile range.</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-with-role" title="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">Variables \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Total \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Non-survivors \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Survivors \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col"><span class="elsevierStyleItalic">p</span> \t\t\t\t\t\t\n \t\t\t\t</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">N</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>522 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">N</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>68 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">N</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>454 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Age, years [median (IQR)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">60.5 (51.0–69.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">62.5 (51.3–71.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">60.0 (51.0–68.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.280 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">Gender, n (%)</span></td><td class="td" title="table-entry " align="left" valign="top">0.319 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Male \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">252 (48.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29 (42.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">223 (49.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Female \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">270 (51.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">39 (57.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">231 (50.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">ACCI, score [median (IQR)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.0 (2.0–5.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.0 (3.0–5.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.0 (2.0–4.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">Primary tumor, n (%)</span></td><td class="td" title="table-entry " align="left" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Head and neck \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">41 (7.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4 (5.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37 (8.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Thoracic \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">132 (25.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13 (19.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">119 (26.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Gastrointestinal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">184 (35.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15 (22.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">169 (37.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Gynaecological \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">52 (10.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14 (20.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">38 (8.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Urological \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23 (4.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2 (2.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21 (4.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Haematological \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">30 (5.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9 (13.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21 (4.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Brain \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10 (1.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2 (2.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8 (1.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Breast \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19 (3.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5 (7.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14 (3.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Others \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">31 (5.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4 (5.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27 (5.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">Clinical stage of cancer, n (%)</span></td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>I \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">64 (12.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0 (0.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">64 (14.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>II \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">180 (34.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16 (23.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">164 (36.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>III \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">155 (29.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15 (22.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">140 (30.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>IV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">123 (23.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37 (54.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">86 (18.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top"><span class="elsevierStyleItalic">History of anticancer therapy, n (%)</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Chemotherapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">223 (42.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33 (48.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">190 (41.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.301 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Radiotherapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">98 (18.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15 (22.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">83 (18.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.457 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Biological therapy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">30 (5.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6 (8.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">24 (5.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.243 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">Patient origin, n (%)</span></td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Emergency department \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">51 (9.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18 (26.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33 (7.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Hospital ward \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">471 (90.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">50 (73.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">421 (92.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">Type of admission, [n (%)]</span></td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Elective surgery \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">390 (74.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21 (30.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">369 (81.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Emergency surgery \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23 (4.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5 (7.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18 (4.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Non-surgery \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">109 (20.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42 (61.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">67 (14.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">Reason for admission, n (%)</span></td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Malignancy-related \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">429 (82.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33 (48.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">396 (87.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Non-malignancy-related \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">93 (17.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">35 (51.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">58 (12.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">APACHE II, score [median (IQR)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.0(10.0–14.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.5(10.5–18.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.0(10.0–14.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.002 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Sepsis</span>,<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a><span class="elsevierStyleItalic">n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37 (7.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16 (23.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21 (4.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Chemotherapy-induced adverse event</span>,<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a><span class="elsevierStyleItalic">n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26 (5.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12 (17.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14 (3.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Mechanical ventilation, n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">81 (15.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">42 (61.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">39 (8.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Length of ICU stay, days [median (IQR)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.0 (2.0–4.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.5 (3.0–8.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.0 (2.0–4.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Length of hospital stay, days [median (IQR)]</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.0 (6.0–14.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.0(4.0–12.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Unplanned ICU re-admission, n (%)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23(4.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8 (11.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15 (3.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.005 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1868924.png" ] ] ] "notaPie" => array:2 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Pneumonia (18 cases), peritonitis (nine cases), soft tissue infection (four cases), urinary tract infection (two cases), central nervous system infection (two cases), unknown site (two cases).</p>" ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "b" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Neutropenia/pancytopenia (nine cases), interstitial pneumonitis (six cases), mucositis (five cases), cardiotoxicity (four cases), neurotoxicity (two cases).</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Characteristics of patients and univariate analysis of hospital mortality.</p>" ] ] 3 => 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">APACHE, Acute Physiology and Chronic Health Evaluation; <span class="elsevierStyleItalic">β</span>, logistic regression coefficient; CI, confidence interval; Ln, natural logarithm; Ref., reference category; SE, standard error of <span class="elsevierStyleItalic">β</span>.</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="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variables \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">β</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">SE \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Wald's statistic \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Odds ratio \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">95% CI \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span> \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Ln (General APACHE II)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.094 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.042 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.01–1.19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.026 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Mechanical ventilation</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.731 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.347 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">61.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">15.34 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7.77–30.28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="7" align="left" valign="top"><span class="elsevierStyleItalic">Clinical stage of cancer</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>I-II \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Ref. \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Ref. \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">10.32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Ref. \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Ref. \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.006 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>III \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.054 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.442 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.02 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.40–2.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.903 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>IV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.049 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.390 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7.24 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.85 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.33–6.12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.007 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Non-malignancy-related admission</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.800 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.365 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">24.37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">6.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.96–12.35 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Constant</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−5.535 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.927 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">35.65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.004 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top"><0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1868922.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Results of selected model (APACHE II for critically ill patients with a solid tumor) in multivariate logistic regression analysis.</p>" ] ] 4 => 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:2 [ "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">APACHE, Acute Physiology and Chronic Health Evaluation; APACHE II<span class="elsevierStyleInf">CCP</span>, APACHE II for critically ill patients with a solid tumor.</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="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Points \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"><span class="elsevierStyleBold">Component 1</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">General APACHE II</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">points \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"><span class="elsevierStyleBold">Component 2</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Mechanical ventilation</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Non-malignancy-related admission</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">Clinical stage of cancer</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>I–II \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>III \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>IV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleBold">Total score (component 1)</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">=</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">0–71</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleBold">Total score (component 2)</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">=</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">0–6</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleBold">Logit</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">=</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">−5.535</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">+</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">0.094</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">*</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">Ln(component 1)</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">+</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">0.93</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">*</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">component 2</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleBold">Estimated risk of mortality</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">=</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">e</span><span class="elsevierStyleSup"><span class="elsevierStyleBold">logit</span></span><span class="elsevierStyleBold">/(1</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">+</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleBold">e</span><span class="elsevierStyleSup"><span class="elsevierStyleBold">logit</span></span><span class="elsevierStyleBold">)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1868923.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">APACHE II<span class="elsevierStyleInf">CCP</span> scoring system.</p>" ] ] 5 => array:5 [ "identificador" => "upi0005" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => false "mostrarDisplay" => true "Ecomponente" => array:2 [ "fichero" => "mmc1.pdf" "ficheroTamanyo" => 125754 ] ] 6 => array:5 [ "identificador" => "eq0005" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "Probability=elogit1+elogit" "Fichero" => "STRIPIN_si1.jpeg" "Tamanyo" => 1716 "Alto" => 35 "Ancho" => 147 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:28 [ 0 => array:3 [ "identificador" => "bib0145" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Intensive care for cancer patients. 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