Nomogram for predicting overall survival after curative gastrectomy using inflammatory, nutritional and pathological factors / Nomograma para predecir la supervivencia global después de una gastrectomía curativa utilizando factores inflamatorios, nutricionales y patológicos

Purpose: To establish a nomogram for predicting the overall survival (OS) in patients with gastric cancer (GC) based on inflammatory, nutritional and pathological factors. Methods: GC patients underwent curative gastrectomy from January 2012 to June 2017 in our hospital were included, and were classified into training set and validation set with a ratio of 7:3. Then variables associated with OS were analyzed using univariate and multivariate Cox regression analysis. Nomograms predicting OS were built using variables from multivariable Cox models. Finally, Kaplan–Meier curve and Log-rank test were also conducted to analyze the 1-yr, 3-yr and 5-yr OS to validate the efficiency of risk stratification of the nomogram. Results: A total of 366 GC patients were included. After univariate and multivariate Cox regression analysis, age (HR = 1.52, 95% CI = 1.01–2.30, P = 0.044), CA50 (HR = 1.90, 95% CI = 1.12–3.21, P = 0.017), PNI (HR = 1.65, 95% CI = 1.13–2.39, P = 0.009), SII (HR = 1.46, 95% CI = 1.03–2.08, P = 0.036), T stage (HR = 2.26, 95% CI = 1.01–5.05, P = 0.048; HR = 7.24, 95% CI = 3.64–14.40, P < 0.001) were independent influencing factors on the survival time of GC patients. Five factors including CEA, prognostic nutritional index (PNI), systemic immune-inflammation index (SII), ln (tumor size), T stage, and N stage were identified and entered the nomogram, which showed good discrimination and calibration in both sets. On internal validation, 1-yr, 3-yr and 5-yr nomogram demonstrated a good discrimination with an area under the ROC curve (AUC) of 0.77, 0.84 and 0.86, respectively. The AUC for 1-yr, 3-yr and 5-yr nomogram in validation set was 0.77, 0.79 and 0.81, respectively. The OS in low risk group of training cohort and validation cohort was significantly higher than that of intermediate risk group and high risk group, respectively...(AU)

A deep learning model for accurately predicting cancer-specific survival in patients with primary bone sarcoma of the extremity: a population-based study

Purpose Primary bone and joint sarcomas of the long bone are relatively rare neoplasms with poor prognosis. An efficient clinical tool that can accurately predict patient prognosis is not available. The current study aimed to use deep learning algorithms to develop a prediction model for the prognosis of patients with long bone sarcoma. Methods Data of patients with long bone sarcoma in the extremities was collected from the Surveillance, Epidemiology, and End Results Program database from 2004 to 2014. Univariate and multivariate analyses were performed to select possible prediction features. DeepSurv, a deep learning model, was constructed for predicting cancer-specific survival rates. In addition, the classical cox proportional hazards model was established for comparison. The predictive accuracy of our models was assessed using the C-index, Integrated Brier Score, receiver operating characteristic curve, and calibration curve. Results Age, tumor extension, histological grade, tumor size, surgery, and distant metastasis were associated with cancer-specific survival in patients with long bone sarcoma. According to loss function values, our models converged successfully and effectively learned the survival data of the training cohort. Based on the C-index, area under the curve, calibration curve, and Integrated Brier Score, the deep learning model was more accurate and flexible in predicting survival rates than the cox proportional hazards model. Conclusion A deep learning model for predicting the survival probability of patients with long bone sarcoma was constructed and validated. It is more accurate and flexible in predicting prognosis than the classical CoxPH model (AU)

Development of a Nomogram Model to Predict the Risk of Stricture Recurrence after Urethroplasty: A Retrospective Study

Objective: A retrospective study was performed to analyse the influencing factors of stricture recurrence after urethroplasty and to establish a predictive nomogram model. Methods: The clinical data of patients who underwent urethroplasty in our hospital from January 2021 to June 2023 were retrospectively analysed. Depending on whether stenosis occurs six months after surgery, the patients were divided into recurrence and nonrecurrence groups. Logistic regression analysis was performed on the indicators with statistically significant differences between the two groups in single factor analysis to analyse the influencing factors of postoperative recurrence risk of stricture. X64.4.1.3 version R language and external source packages were used to build the nomogram model. The nomogram was internally validated through 10-fold cross-validation, and C-index was calculated. The area under the curve (AUC) of the receiver operating characteristic curve was employed to evaluate the results of the internal validation. Results: Amongst 105 patients who underwent urethroplasty in our hospital, 15 patients with recurrence were included in the recurrence group, and 90 patients without recurrence were included in the nonrecurrence group. The length of stricture segment, history of urethroplasty and smoking history within 3 months before surgery were risk factors for stricture recurrence, with odds ratio (OR) values of 1.874 (95% CI: 1.103–5.725), 1.670 (95% CI: 1.105–2.904) and 1.740 (95% CI: 1.456–5.785), respectively. The constructed nomogram obtained an average AUC of 0.842 and an average C-index of 0.794, calculated after 200 times of 10-fold cross-validation. Conclusions: From the data of this study, it can be deduced that the influencing factors of stricture recurrence after urethroplasty include the length of stricture segment, history of urethroplasty and smoking history of 3 months before surgery... (AU)

A nomogram based on 4-lncRNAs signature for improving prognostic prediction of hepatocellular carcinoma

Purpose Long noncoding RNAs (lncRNAs) with abnormal expression are frequently seen in hepatocellular cancer patients (HCC). Previous studies have reported the correlation between lncRNA and prognosis processes of HCC patients. In this research, a graphical nomogram with lncRNAs signatures, T, M phases was developed using the rms R package to estimate the survival rates of HCC patients in year 1, 3, and 5. Methods To find the prognostic lncRNA and create the lncRNA signatures, univariate Cox survival analysis and multivariate Cox regression analysis were chosen. The rms R software package was used to build a graphical nomogram based on lncRNAs signatures to predict the survival rates in of HCC patients in 1, 3, and 5 years. Using “edgeR”, “DEseq” R packages to find the differentially expressed genes (DEGs). Results Firstly, a total of 5581 DEGs including 1526 lncRNAs and 3109 mRNAs were identified through bioinformatic analysis, of which 4 lncRNAs (LINC00578, RP11-298O21.2, RP11-383H13.1, RP11-440G9.1) were identified to be strongly related to the prognosis of liver cancer (P < 0.05). Moreover, we constructed a 4-lncRNAs signature by using the calculated regression coefficient. 4-lncRNAs signature is identified to significantly correlated with clinical and pathological characteristics (such as T stage, and death status of HCC patients). Conclusions A prognostic nomogram on the base of 4-lncRNAs markers was built, which is capable to accurately predict the 1-year, 3-year, and 5-year survival of HCC patients after the construction of the 4-lncRNAs signature linked with prognosis of HCC (AU)

Development and validation of a nomogram to predict non-response to 5-aminosalicylic acid in patients with ulcerative colitis

Background: there are some patients with ulcerative colitis (UC) who have non-response (NR) to 5-aminosalicylic acid (5-ASA). To promote individualized treatment in UC patients, it is crucial to identify valid predictors to estimate NR to 5-ASA. Therefore, this study aimed to identify the predictive value of clinical and biochemical markers and to construct a nomogram model predicting NR to 5-ASA in patients with UC. Methods: data of patients diagnosed with UC in the First Hospital of China Medical University between January 2012 and December 2020 were retrospectively analyzed. Primary outcome was the proportion of NR to 5-ASA. Multivariable logistic regression was used to construct prediction models. Area under the curve (AUC), calibration and decision curve analyses (DCA) were assessed in the validation cohort. Results: of 284 UC patients who were treatment-naive, 86 (30.3 %) had NR to 5-ASA. Univariate regression analysis showed that disease classification (DC) (p = 0.008), monocytes (MONO) (p = 0.041), platelet distribution width (PDW) (p = 0.027), serum total cholesterol (TC) (p = 0.031) and α1 globulin (p < 0.001) were strongly associated with NR to 5-ASA. Receiver operating characteristics (ROC) analysis indicated the AUC was 0.852, it showed that this model has a good degree of discrimination. The DCA curve showed that the predicted probability is 0.0-96.0 %. Conclusion: this study developed a predictive model with good discrimination and calibration, and high clinical validity, which can effectively estimate the risk of NR to 5-ASA. DC, MONO, PDW, TC and α1 globulin can be used as predictors for NR to 5-ASA in UC patients. (AU)

Development and validation of a prognostic nomogram for the renal relapse of lupus nephritis / Desarrollo y validación de un nomograma pronóstico para la recaída renal de la nefritis lúpica

Objectives This study aims to assess the risk of relapse after complete remission (CR) and partial remission (PR), and to develop a prognostic nomogram predicting the probability in lupus nephritis (LN) patients. Methods Data from patients with LN who had been in remission were collected as a training cohort. The prognostic factors were analyzed using the univariable and multivariable Cox model for the training group. A nomogram was then developed using significant predictors in multivariable analysis. Both discrimination and calibration were assessed by bootstrapping with 100 resamples. Results A total of 247 participants were enrolled, including 108 in the relapse group and 139 in the no relapse group. In multivariate Cox analysis, Systemic Lupus Erythematosus Disease Activity Index (SLEDAI), erythrocyte sedimentation rate (ESR), complement 1q (C1q), and antiphospholipid (aPL), anti-Sm antibody were found to be significant for predicting relapse rates. The prognostic nomogram including the aforementioned factors effectively predicted 1- and 3-year probability of flare-free. Moreover, a favorable consistency between the predicted and actual survival probabilities was demonstrated using calibration curves. Conclusions High SLEDAI, ESR, and positive aPL, anti-Sm antibody are potential risk factors for LN flare, while high C1q can reduce its recurrence. The visualized model we established can help predict the relapse risk of LN and aid clinical decision-making for individual patients (AU)

Objetivos Este estudio pretende evaluar el riesgo de recaída tras la remisión completa y la remisión parcial, y desarrollar un nomograma pronóstico que prediga la probabilidad en pacientes con nefritis lúpica (NL). Métodos Se recogieron datos de pacientes con NL que habían estado en remisión como cohorte de entrenamiento. Se analizaron los factores pronósticos utilizando el modelo COX univariable y multivariable para el grupo de entrenamiento. A continuación se desarrolló un nomograma utilizando los predictores significativos en el análisis multivariable. Tanto la discriminación como la calibración se evaluaron mediante bootstrapping con 100 remuestreos. Resultados Se inscribió a un total de 247 participantes, incluidos 108 en el grupo de recaída y 139 en el grupo sin recaída. En el análisis multivariante de Cox, el índice de actividad de la enfermedad lúpica eritematosa sistémica (SLEDAI), la velocidad de sedimentación globular (VSG), el complemento 1q (C1q) y los anticuerpos antifosfolípidos (aPL) y anti-Sm resultaron significativos para predecir las tasas de recaída. El nomograma pronóstico que incluía los factores mencionados predijo eficazmente la probabilidad a 1 y a 3 años de estar libre de reagudizaciones. Además, se demostró una coherencia favorable entre las probabilidades de supervivencia previstas y las reales mediante curvas de calibración. Conclusiones SLEDAI alto, VSG y aPL positivo, anticuerpos anti-Sm son factores de riesgo potenciales de reagudización de la NL, mientras que C1q alto puede reducir su recurrencia. El modelo visualizado que establecimos puede ayudar a predecir el riesgo de recidiva de la NL y ayudar a la toma de decisiones clínicas para pacientes individuales (AU)

A novel nomogram integrated with PDL1 and CEA to predict the prognosis of patients with gastric cancer

Introduction This study aimed to develop a prognostic nomogram for patients with gastric cancer (GC) based on the levels of programmed death 1 ligand 1 (PDL1) and carcinoembryonic antigen (CEA). Methods The nomogram was developed using data from a primary cohort of 247 patients who had been clinicopathologically diagnosed with GC, as well as a validation cohort of 63 patients. Furthermore, the nomogram divided the patients into three different risk groups for overall survival (OS)—the low-risk, middle-risk, and high-risk groups. Univariate and multivariate Cox hazard analyses were used to determine all of the factors included in the model. Decision curve analysis and receiver operating characteristic (ROC) curves were used to assess the accuracy of the nomogram. Results The Kaplan–Meier survival analysis revealed that metastasis stage, clinical stage, and CEA and PDL1 levels were predictors for progress-free survival (PFS) and OS of patients with GC. Metastasis stage, clinical stage, and CEA and PDL1 levels were found to be independent risk factors for the PFS and OS of patients with GC in a multivariate analysis, and the nomogram was based on these factors. The concordance index of the nomogram was 0.763 [95% confidence interval (CI) 0.740–0.787]. The area under the concentration–time curve of the nomogram model was 0.81 (95% CI 0.780–0.900). According to the decision curve analysis and ROC curves, the nomogram model had a higher overall net efficiency in forecasting OS than clinical stage, CEA and PDL1 levels. Conclusion In conclusion, we proposed a novel nomogram that integrated PDL1 and CEA, and the proposed nomogram provided more accurate and useful prognostic predictions for patients with GC (AU)

A Survival Model for Patients with Upper Tract Urothelial Carcinoma

Objectives: We aimed to establish a survival model for patients with upper tract urothelial carcinoma (UTUC). Methods: A total of 241 patients with UTUC treated from January 2010 to December 2018 were selected. Their general clinical data were collected, and urological indices were measured. They were followed up after discharge, and divided into a death group (n = 51) and a survival group (n = 190) to compare the clinical data. Multivariate logistic regression analysis was performed to analyze the independent risk factors for postoperative death, based on which a nomogram prediction model was established and then validated. Results: The death group had significantly older age, larger tumor diameter, and higher tumor grade, pathological stage and proportion of no adjuvant chemotherapy than those of the control group (p < 0.01). The results of multivariate logistic analysis suggested that high tumor grade, tumor located in the ureter, large tumor diameter, high pathological stage, and lymph node metastasis were independent risk factors for postoperative death. A nomogram prediction model was established based on the prognostic independent risk factors. The area under the curve of receiver operating characteristic curve was 0.828 (95% confidence interval (CI): 0.801–0.845), so the model had good discrimination. The calibration curve showed that the model had high consistency. Conclusions: The established nomogram model can be used to predict the mortality risk of patients with UTUC and postoperative survival, and to develop individualized treatment plans for improving the prognosis and survival (AU)

Metabolic Syndrome Predicts Uric Acid Stones in the Upper Urinary Tract: Development and Validation of a Nomogram Model

Background: Accurately identifying uric acid stones is pivotal in determining the appropriate treatment strategy for patients. This study aimed to design an innovative nomogram to predict the occurrence of uric acid stones in the upper urinary tract. Methods: This retrospective study examined 680 patients with urinary stones from October 2019 to September 2022. Risk factors were identified through univariate and multivariate logistic regression, leading to the development of a nomogram. This model’s validity was then assessed internally using receiver operating characteristic (ROC) curves, the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Results: Our findings revealed that metabolic syndrome (odds ratio (OR) = 4.347, 95% confidence interval (CI) 1.306–14.466, p = 0.017), serum urea levels (OR = 1.004, 95% CI 1.143–2.002, p = 0.004), urinary pH (OR = 0.185, 95% CI 0.059–0.583, p = 0.004), urinary potassium (OR = 0.926, 95% CI 0.875–0.981, p = 0.009), and urinary calcium (OR = 0.693, 95% CI 0.492–0.977, p = 0.037) are independent factors for upper urinary tract uric acid stones. Utilizing the five variables, we developed a predictive nomogram. The AUC of the training cohort and the validation cohort were 0.917 (95% CI 0.871–0.963) and 0.914 (95% CI 0.850–0.978), respectively. Calibration curves indicated strong consistency in both cohorts, and the DCA revealed the model’s clinical utility. Conclusions: We devised a reliable and user-friendly nomogram to predict uric acid stones in the upper urinary tract. It is based on metabolic syndrome, serum biochemical markers, and 24-hour urinary parameters. Key determinants include metabolic syndrome, serum urea, urinary pH, urinary potassium and urinary calcium (AU)

Identification of a cuproptosis-related lncRNA prognostic signature in lung adenocarcinoma

Purpose Cuproptosis-related long non-coding RNA (lncRNA) diseases are associated with the occurrence and development of tumors. This study aimed to investigate whether cuproptosis-related lncRNA can predict the prognosis of patients with lung adenocarcinoma (LUAD). Methods Cuproptosis-related lncRNA prognosis (CLPS) model was successfully constructed through cox regression and lasso regression analyses. Then, the prognostic value of CLPS model was tested through the survival analysis, the ROC curve and the nomogram. Finally, the correlation of CLPS model with tumor immunity and tumor mutation burden was analyzed, and the potential susceptibility of drugs for LUAD were predicted. Results CLPS model for LUAD (AC090948.1, CRIM1-DT, AC026356.2, AC004832.5, AL161431.1) was successfully constructed, which has an independent prognostic value. Furthermore, the risk score of CLPS model was correlated with tumor immune characteristics and immune escape, which can predict the sensitivity of drugs including Cisplatin, Etoposide, Gemcitabine, and Erlotinib. Conclusions In conclusion, it was found that CLPS model was associated with tumor immunity and tumor mutation load, which also predicted four potentially sensitive drugs for LUAD patients at different risks (AU)

Non-inferior efficacy of non-surgical treatment to surgical treatment in patients with nonmetastatic head and neck rhabdomyosarcoma: a SEER-based study

Purpose Head and neck rhabdomyosarcoma (HNRMS) is a rare but aggressive malignant neoplasm. Given the young patient age and critical anatomy of the head and neck, performing surgery on the primary tumor still remains debatable. This study aimed to evaluate the impact of the non-surgery-based treatment versus surgery-based treatment on patients with nonmetastatic HNRMS. Methods Patients diagnosed with nonmetastatic HNRMS between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled in our study. Inverse probability treatment weighting (IPTW) method was employed to balance confounding factors between surgery and non-surgery groups. Kaplan–Meier methods and COX regression analyses were used to analyze survival outcomes of overall survival (OS) and cancer-specific survival (CSS). Prognostic nomogram was established to predict survival. Results A total of 260 eligible patients were extracted from the SEER database. Kaplan–Meier survival curves revealed that there was no significant difference in OS and CSS between the surgery and non-surgery groups both before and after IPTW (p > 0.05). Cox regression analyses and IPTW-adjusted Cox regression analyses for both OS and CSS showed similar survival between the two groups. Prognostic factors were explored and a nomogram for patients in the surgery group was constructed. Risk stratification based on the nomogram indicated that patients in surgery-high-risk group did not benefit from primary surgery. While those in surgery-low-risk group had an equal survival outcome to those in non-surgery group. Conclusions Our study revealed that compared to patients receiving surgery, those not receiving surgery had similar survival outcomes for nonmetastatic HNRMS. Our established nomogram may serve as a practical tool for individual prognostic evaluations (AU)

Validación externa de los sistemas de puntuación actuales y desarrollo de un nuevo sistema de puntuación para la predicción de la tasa libre de cálculos tras la cirugía intrarrenal retrógrada en pacientes con un diámetro acumulado del cálculo de 2-4 cm / External validation of the current scoring systems and development of a novel scoring system to predict stone-free rates after retrograde intrarenal surgery in patients with cumulative stone diameter of 2-4 cm

Objetivo Nuestro objetivo principal es realizar la validación externa de los sistemas de puntuación actuales para predecir el estado libre de cálculos (ELC) después de la cirugía intrarrenal retrógrada (CRIR) para cálculos renales de 2-4 cm y desarrollar un nuevo sistema de puntuación reexaminando los posibles factores predictivos relacionados con el ELC. Métodos Se evaluaron retrospectivamente los pacientes que recibieron CRIR para el tratamiento de cálculos renales con diámetro acumulado de 2-4 cm, entre enero de 2017 y marzo de 2021. Los cálculos residuales ≤ 2 mm se definieron como clínicamente insignificantes, y estos casos se consideraron como ELC. Se examinaron los posibles factores predictivos relacionados con el ELC mediante el análisis de regresión logística multivariante. Se elaboró un nomograma y se creó un sistema de puntuación utilizando variables predictivas independientes. Mediante el análisis ROC se evaluó la capacidad de predicción de los sistemas de puntuación actuales y del recién desarrollado. Resultados Los sistemas de puntuación existentes resultaron insuficientes para predecir el ELC (AUC < 0,660 en todos los casos). Se identificaron como predictores independientes del ELC el área de superficie (OR: 0,991, p < 0,001), la densidad (OR: 0,998, p < 0,001), el número (OR: 0,365, p = 0,033) y la localización de los cálculos (p = 0,037). Utilizando estos marcadores predictivos, se desarrolló un nuevo sistema de puntuación cuyos resultados oscilan entre 4 y 15. El valor AUC de este sistema de puntuación fue de 0,802 (0,734-0,870). Conclusión Los sistemas de puntuación RUSS, S-ReSC y RIRS y el nomograma de Ito no lograron predecir el ELC en cálculos de > 2 cm. Nuestro nuevo sistema de puntuación tuvo una capacidad predictiva del ELC mayor en cálculos de > 2 cm, en comparación con los otros sistemas de puntuación (AU)

Objective Our primary aim is to perform the external validation of the current scoring systems in predicting stone-free status (SFS) after retrograde intrarenal surgery (RIRS) for renal stones 2-4 cm and develop a novel scoring system by re-examining possible predictive factors related to SFS. Methods Patients who underwent RIRS due to renal stones with a cumulative stone diameter of 2-4 cm between January 2017 and March 2021 were retrospectively screened. Residual stones ≤ 2 mm were defined as clinically insignificant, and these cases were considered to have SFS. Possible predictive factors related to SFS were examined using the multivariate logistic regression analysis. A nomogram and a scoring system were developed using independent predictive variables. The prediction ability of the previous and the new scoring system were evaluated with the ROC analysis. Results The existing scoring systems were found to be insufficient in predicting SFS (AUC < 0.660 for all). The independent predictors of SFS were identified as stone surface area (OR: 0.991, p < 0.001), stone density (OR: 0.998, p < 0.001), number of stones (OR: 0.365, p = 0.033), and stone localization (p = 0.037). Using these predictive markers, a new scoring system with a score ranging between 4 and 15 was developed. The AUC value for this scoring system was 0.802 (0.734-0.870). Conclusion The RUSS, S-ReSC and RIRS scoring systems and Ito's nomogram failed to predict SFS in stones > 2 cm. The SFS predictive ability of our new scoring system was higher in > 2 cm stones compared to the other scoring systems (AU)

A novel metabolism-related prognostic gene development and validation in gastric cancer

Background The importance of metabolism-related alterations in the development of gastric cancer (GC) is increasingly recognized. The present study aimed to identify metabolism-related genes to facilitate prognosis of GC patients. Methods Gene expression datasets and clinical information of GC patients were downloaded from TCGA and GEO databases. We scored the enrichment of human metabolism-related pathways (n = 86) in GC samples by GSV, constructed prognostic risk models using LASSO algorithm and multivariate Cox regression analysis, combined with clinical information to construct a nomogram, and finally cis score algorithm to analyze the abundance of immune-related cells in different subtypes. We used Weka software to screen for prognosis-related marker genes and finally validated the expression of the selected genes in clinical cancer patient tissues. Results We identified that two GC metabolism-related signatures were strongly associated with OS and the levels of immune cell infiltration. Moreover, a survival prediction model for GC was established based on six GC metabolism-related genes. Time-dependent ROC analysis showed good stability of the risk prediction scoring model. The model was successfully validated in an independent ACRG cohort, and the expression trends of key genes were also verified in the GC tissues of patients. DLX1, LTBP2, FGFR1 and MMP2 were highly expressed in the cluster with poorer prognosis while SLC13A2 and SLCO1B3 were highly expressed in the cluster with better prognosis. Conclusions We identified a risk predictive score model based on six metabolism-related genes related to survival, which may serve as prognostic indicators and potential therapeutic targets for GC (AU)

¿Son suficientes los nomogramas actuales para predecir los resultados de la litotricia por ondas de choque? / Are the current nomograms sufficient to predict shockwave lithotripsy outcomes?

Introducción y objetivos: Investigar los factores que afectan los resultados del tratamiento con LEOCH, validar tres nomogramas actuales (Kim JK, Triple D y S3HoCKwave) y comparar la capacidad predictiva de los nomogramas para los resultados de la LEOCH en los cálculos del tracto urinario superior.Pacientes y métodosSe revisaron retrospectivamente las historias clínicas de los pacientes con cálculos renales y ureterales proximales tratados con LEOCH entre marzo de 2013 y octubre de 2020. Se analizaron los factores que afectan al éxito de LEOCH con un análisis de regresión logística multivariante y se compararon los tres sistemas de puntuación con el área bajo la curva (AUC).ResultadosNuestro estudio incluyó un total de 580 pacientes. La tasa global de eliminación de cálculos fue del 61% y 144/580 pacientes (24,8%) estaban libres de cálculos tras una sesión. En el análisis de regresión logística multivariante, la ubicación del cálculo en el cáliz superior (OR: 2,988; IC 95%: 1,350-6,612; p=0,007), en el cáliz medio (OR: 3,036; IC 95%: 1,472-6,258; p=0,003) y en el cáliz inferior (OR: 2,131; IC 95%: 1,182-3,839; p=0,012), así como el número de cálculos (OR: 1,663; IC 95%: 1,140-2,425; p=0,008), el diámetro máximo del cálculo (OR: 1,156; IC 95%: 1,098-1,217; p<0,001) y el valor máximo de unidades Hounsfield (OR: 1,001; IC 95%: 1,001-1,002; p<0,001) fueron factores de riesgo independientes del fracaso de LEOCH. Las AUC de las puntuaciones Kim JK, Triple D y S2HoCKwave para predecir el éxito de la LEOCH fueron de 0,678, 0,548 y 0,626, respectivamente (AU)

Introduction and objectives: To investigate factors affecting SWL outcomes, validate three current nomograms (Kim JK, Triple D and S3HoCKwave) and compare the predictive ability of the nomograms for SWL outcomes in upper urinary tract stones.Patients and methodsMedical records of patients with renal and proximal ureteral stones treated with SWL between March 2013 and October 2020 were retrospectively reviewed. Factors affecting SWL success were analyzed with multivariate logistic regression analysis and the three predictive scoring systems compared with the area under the curve (AUC).ResultsA total of 580 patients were included in our study. The overall stone free rate was 61% and 144/580 patients (24.8%) were stone free after one session. In multivariate logistic regression analysis, stone location at upper calyx (OR:2.988; 95%Cl: 1.350–6.612; p=0.007), middle calyx (OR:3.036; 95%Cl: 1.472–6.258; p=0.003), and lower calyx (OR:2.131; 95%Cl: 1.182–3.839; p=0.012), as well as number of stones (OR:1.663; 95%Cl: 1.140–2.425; p=0.008), maximum diameter of stone (OR:1.156; 95%Cl: 1.098–1.217; p<0.001) and maximum Hounsfield Unit (OR:1.001; 95%Cl: 1.001–1.002; p<0.001) were independent risk factors of SWL failure. The AUCs of the Kim JK, Triple D and S2HoCKwave scores for predicting SWL success were 0.678, 0.548, and 0.626 respectively.ConclusionsStone location, number, maximal diameter, and maximum HU were independent predictive factors for SWL outcome in the treatment of upper urinary tract stones. Current nomograms, Kim JK nomogram, Triple D score and S3HoCKwave score can predict treatment success after SWL, but all of them have poor discrimination according to AUC analysis. (AU)

A novel nomogram based on the nutritional risk screening 2002 score to predict survival in hepatocellular carcinoma treated with transarterial chemoembolization / Un nuevo nomograma basado en el puntaje de detección de riesgo nutricional 2002 para predecir la supervivencia en el carcinoma hepatocelular tratado con quimioembolización transarterial

Objective: transarterial chemoembolization (TACE) is one of the common treatments for hepatocellular carcinoma (HCC). Predicting prognosis for HCC patients who received TACE is challenging because of huge differences in outcome. At present, the Nutritional Risk Screening 2002 (NRS-2002) is widely used to screen nutritional risk in hospitalized patients, which has been confirmed to be related to prognosis. Here, the objective of this research is to construct a prognostic nomogram using the NRS-2002 score for HCC patients receiving TACE. Methods: we enrolled 359 HCC patients who received TACE at the Xingtai People's Hospital between January 2015 and December 2020. According to the preoperative NRS-2002 score, patients were divided into an NRS ≥ 3 group (n = 190; 52.9 %) and an NRS < 3 group (n = 167, 47.1 %). Meanwhile, variables associated with survival were analyzed by univariate and multivariate Cox regression. Beyond that, a nomogram incorporating independent variables was established. The concordance index (C-index) and calibration curves were used to assess the prediction performance of the nomogram. Results: the median survival of the NRS ≥ 3 group was significantly lower than that of the NRS < 3 group. As shown by multivariate analysis, in the Barcelona Clinic Liver Cancer stage an NRS-2002 score ≥ 3, γ-glutamyl transpeptidase, and alpha-fetoprotein were significantly associated with survival in HCC patients after TACE. In addition, the C-index was 0.708 (95 % confidence interval: 0.672-0.743), and the calibration curves showed a good consistency between the observed and predicted survivals at 1, 2, and 3 years, respectively. Conclusions: NRS-2002 ≥ 3 could identify high-risk patients with HCC who received TACE. The NRS-2002-based nomogram model had good prognostic prediction accuracy(AU)

Objetivo: la quimioembolización transarterial (TACE) es uno de los tratamientos comúnmente utilizados para el carcinoma hepatocelular (CHC). La predicción pronóstica en pacientes con CHC sometidos a TACE es un desafío debido a la gran variabilidad del resultado. La “Detección del riesgo nutricional 2002” (NRS-2002) se utiliza ampliamente en la actualidad para evaluar el riesgo nutricional de los pacientes hospitalizados y se ha demostrado que está relacionada con el pronóstico. Aquí, nuestro objetivo fue construir un nomograma pronóstico, utilizando la puntuación NRS-2002, para pacientes con HCC que reciben TACE. Métodos: reclutamos a 359 pacientes con CHC tratados con TACE en el Hospital Popular de Xingtai desde enero de 2015 hasta diciembre de 2020. Los pacientes se dividieron en un grupo NRS ≥ 3 (n = 190; 52,9 %) y un grupo NRS < 3 (n = 167, 47,1 %) según la puntuación NRS-2002 preoperatoria. Las variables asociadas con la supervivencia se analizaron mediante la regresión de Cox univariante y multivariante. Se estableció un nomograma que incorpora variables independientes. El rendimiento predictivo del nomograma se evaluó mediante el índice de concordancia (índice C) y la curva de calibración. Resultados: la mediana de supervivencia del grupo NRS ≥ 3 fue significativamente menor que la del grupo NRS < 3. El análisis multivariante mostró que el estadio del grupo de Clínica de Cáncer de Hígado de Barcelona, una puntuación NRS-2002 ≥ 3, la γ-glutamil transpeptidasa y la alfa-fetoproteína se asociaron significativamente con la supervivencia de los pacientes con CHC después de la TACE. El índice C fue de 0,708 (intervalo de confianza del 95 %: 0,672-0,743) y las curvas de calibración mostraron una buena concordancia entre las supervivencias observadas y las predichas a 1, 2 y 3 años. Conclusiones: la puntuación NRS-2002 ≥ 3 podría identificar a los pacientes con HCC de alto riesgo sometidos a TACE (AU)

Identification of a novel cancer microbiome signature for predicting prognosis of human breast cancer patients

BackgroundPrognosis of breast cancer (BC) patients differs considerably and identifying reliable prognostic biomarker(s) is imperative. With evidence that the microbiome plays a critical role in the response to cancer therapies, we aimed to identify a cancer microbiome signature for predicting the prognosis of BC patients.MethodsThe TCGA BC microbiome data (TCGA-BRCA-microbiome) was downloaded from cBioPortal. Univariate and multivariate Cox regression analyses were used to examine association of microbial abundance with overall survival (OS) and to identify a microbial signature for creating a prognostic scoring model. The performance of the scoring model was assessed by the area under the ROC curve (AUC). Nomograms using the microbial signature, clinical factors, and molecular subtypes were established to predict OS and progression-free survival (PFS).ResultsAmong 1406 genera, the abundances of 94 genera were significantly associated with BC patient OS in TCGA-BRCA-microbiome dataset. From that set we identified a 15-microbe prognostic signature and developed a 15-microbial abundance prognostic scoring (MAPS) model. Patients in low-risk group significantly prolong OS and PFS as compared to those in high-risk group. The time-dependent ROC curves with MAPS showed good predictive efficacy both in OS and PFS. Moreover, MAPS is an independent prognostic factor for OS and PFS over clinical factors and PAM50-based molecular subtypes and superior to the previously published 12-gene signature. The integration of MAPS into nomograms significantly improved prognosis prediction.ConclusionMAPS was successfully established to have independent prognostic value, and our study provides a new avenue for developing prognostic biomarkers by microbiome profiling.

Factores para predecir los resultados de la litotricia por ondas de choque en pacientes pediátricos y validación externa de un nomograma / Factors to predict shock-wave lithotripsy results in pediatric patients and external validation of a nomogram

OBJETIVO: Evaluar la exactitud del nomograma de Dogan para predecir la tasa libre de cálculos (LC) tras una única sesión de litotricia extracorpórea por ondas de choque (LEOCH) y evaluar factores predictivos de los resultados de LEOCH en niños. PACIENTES Y MÉTODOS: En el estudio participaron 68 pacientes menores de 18 años que habían sido tratados con LEOCH en nuestro centro terciario desde enero de 2010 hasta diciembre de 2016, por cálculos radiopacos del tracto urinario superior. La media de edad fue de 50 meses (6-207) y la media del período de seguimiento, de 9 meses (4-50). Se excluyeron los pacientes con litiasis cistínica, anomalía renal, derivación urinaria y litiasis múltiples localizadas en diferentes cálices, igual que en el estudio del nomograma original. El estatus LC se evaluó mediante la realización de radiografía simple de abdomen y ecografía urinaria 2 semanas después de cada sesión de LEOCH. Los pacientes que estaban completamente libres de cálculos fueron considerados LC. Se realizaron análisis de regresión logística múltiple para determinar las variables que afectan el estado de LC. El método bootstrap con 1.000 repeticiones se utilizó para la validación externa del nomograma desarrollado por Dogan. RESULTADOS: Las tasas de LC para cada sesión de LEOCH fueron de 54,4% (37/68) para la primera sesión, de 33,3% (7/21) para la segunda y de 55,6% (5/9) para la tercera. En total, la tasa de LC fue del 72,1% (49/68). El análisis de regresión logística múltiple mostró correlaciones positivas y significativas entre la edad y el tamaño del cálculo, y el riesgo de fracaso al tratamiento con LEOCH. El gráfico de calibración externa mostró una validación aceptable respecto al nomograma de Dogan para predecir el fracaso de LEOCH en la primera sesión. CONCLUSIÓN: Nuestro estudio demostró que el nomograma de Dogan se puede utilizar para predecir el estado LC tras una sesión de LEOCH en pacientes pediátricos

OBJECTIVE: To evaluate the accuracy of the Dogan nomogram in predicting stone-free (SF) rate after a single shock wave lithotripsy (SWL) session and evaluate factors that predict SWL results in children. PATIENTS AND METHODS: The study included 68 patients under 18 years of age who had been treated with SWL for radiopaque upper urinary tract stones in our tertiary centre from January 2010 to December 2016. The median age is 50 (6-207) months and median follow-up period is 9 (4-50) months. Patients with known cystine stone disease, abnormal renal anatomy, urinary diversion and multiple stones located in different calyces were excluded like in the original nomogram study. SF status was evaluated by performing plain abdominal radiography and urinary ultrasonography 2 weeks after each SWL session. Patients who were completely free of stones were considered to be SF. Multiple logistic regression analyses were performed to determine the variables affecting SF status. The bootstrap method with 1,000 replicates was used for the external validity of a nomogram developed by Dogan. RESULTS: SF rates for each SWL session were determined as 54.4% (37/68) for the first session, 33.3% (7/21) for the second session and 55.6% (5/9) for the third session. Overall, the SF rate was 72.1% (49/68). Multiple logistic regression analysis showed positive and significant correlations of age and stone size with risk of SWL failure. The external calibration plot showed a nearly good validation with Dogan nomogram to predict SWL failure in first session. CONCLUSION: Our study demonstrates that the Dogan nomogram can be used to predict the SF status after one session of SWL in pediatric patients

Impacto del grado de cumplimiento de un protocolo ERAS en la recuperación funcional después de cirugía colorrectal / ERAS protocol compliance impact on functional recovery in colorectal surgery

INTRODUCCIÓN: El grado de cumplimiento de los protocolos de Enhanced Recovery After Surgery (ERAS) es una medida de calidad del proceso, que además se asocia a mejores resultados. El objetivo del presente estudio es analizar la relación existente entre el grado de cumplimiento del protocolo, el estrés quirúrgico y la recuperación funcional. Se plantea como objetivo secundario, la identificación de factores independientes asociados a la recuperación funcional. MÉTODOS: Estudio retrospectivo observacional unicéntrico de pacientes sometidos a cirugía colorrectal programada dentro de un programa ERAS entre enero de 2017 y junio de 2018. Se analizó el grado de cumplimiento del protocolo porcentual y su relación con el estrés quirúrgico (definido por los niveles plasmáticos de proteína C reactiva al tercer día), y la recuperación funcional (definida por el cumplimiento de los criterios de alta el quinto día postoperatorio o antes). Se llevó a cabo un análisis multivariante de factores independientes asociados a recuperación funcional. RESULTADOS: Se analizaron 313 pacientes. Por cada punto porcentual de cumplimiento adicional del protocolo disminuye 1,46 mg/dL la proteína C reactiva del tercer día y aumenta un 7% la probabilidad de cumplir criterios de alta (p < 00,1 ambos). Los factores asociados a recuperación funcional fueron ASA III-IV (OR 0,26; 0,14-0,48), puntuación CR-POSSUM quirúrgico (OR 0,68; 0,57-0,83), movilización precoz (OR 4,22; 1,43-12,4) y retirada precoz de sonda vesical (OR 3,35; 1,79-6,27), todos ellos p < 0,001. CONCLUSIÓN: El aumento del grado de cumplimiento del protocolo ERAS en cirugía colorrectal, disminuye el estrés quirúrgico y acelera la recuperación funcional

INTRODUCTION: Compliance to ERAS protocols is a process quality measure that is associated to better outcomes. The main objective of this study is to analyze the association between protocol compliance, surgical stress and functional recovery. The secondary objective is to identify independent factors associated to functional recovery. METHODS: A prospective observational single-centre study was performed. Patients who had scheduled colorectal surgery within an ERAS program from January 2017 to June 2018 were included. We analysed the relationship between protocol compliance percentage and surgical stress (defined by C reactive protein [CRP] blood levels on postoperative 3rd day), and functional recovery (defined by the proportion of patients who meet the discharge criteria on the 5th PO day or before). Multivariate analysis was performed to asses independent factor associated to functional recovery. RESULTS: 313 were included. For every additional percentage point of compliance to the protocol 3rd day C reactive protein plasmatic level decreases 1,46 mg/dL and increases 7% the probability to meet the discharge criteria (p < 0.001 both). Independent factors associated to functional recovery were ASA III-IV (OR 0.26; 0.14-0.48), surgical CR-POSSUM score (OR 0.68; 0.57-0.83), early mobilization (OR 4.22; 1.43-12.4) and removal of urinary catheter (OR 3.35; 1.79-6.27), p < 0,001 each of them. CONCLUSION: Better copliance to ERAS protocol in colorectal surgery decreases surgical stress and accelerates functional recovery

Variabilidad de la frecuencia cardíaca como indicador de carga interna en mujeres no deportistas: estudio piloto / Heart rate variability as an indicator of internal load in non-athlete women: pilot study

La variabilidad de la frecuencia cardiaca (VFC) es una herramienta no invasiva que permite evaluar la modulación simpática y parasimpática y se ha propuesto como un método válido para valorar la respuesta individual a una carga de trabajo y, por tanto, la carga de entrenamiento. El objetivo es utilizar la RMSSD-Slope (La pendiente de la raíz cuadrada de la media de las diferencias de la suma de los cuadrados entre intervalos RR adyacentes) para analizar la recuperación tras dos intensidades diferentes en tapiz rodante en mujeres no deportistas, como medida de carga interna (CI) y su posible relación con la carga externa (CE).Participaron 9 mujeres sanas, físicamente activas. Se realizaron dos test, separados entre sí por 48-72 h. El primero fue una prueba máxima en tapiz rodante, en el que se determinó la velocidad aeróbica máxima (VAM). En la segunda sesión, se realizó una prueba al 80% de la VAM. En cada una de las sesiones se hizo un seguimiento la escala de Borg y de la VFC (reposo, ejercicio y recuperación) para su posterior análisis con la RMSSD-Slope.El valor de la RMSSD-Slope en la prueba del 80% de intensidad fue de 0,97 (±0,78), y en la Prueba Máxima fue 0,84 (±0,36). Ambas pruebas presentan una R2 con la escala de Borg (0,62 y 0,62) respectivamente. En el caso de la R2 entre la CE y la RMSSD-Slope fue de 0,04 y 0,14 respectivamente. La pendiente de recuperación de la RMSSD es una buena herramienta de valoración de CI en mujeres físicamente activas pero no deportistas

Heart rate variability (HRV ) is a non-invasive tool capable to evaluate the sympathetic and parasympathetic modulation and it has been proposed as a valid method to assess the individual response to a workload and, therefore, the training load. The objective is to use the RMSSD-Slope (square root of the mean of the differences of the sum of the squares between adjacent RR intervals) to analyze the recovery after two different treadmill intensities in non-athletic women, as an internal training load (ITL) measure and its possible relation with the external training load (ETL) 9 healthy, physically active women participated in the study. Two tests were performed, separated from each other for 48-72h. The first was a maximum treadmill test, in which the maximal aerobic speed (MAS) was determined. In the second session, an 80% test of the MAS was carried out. In each of the sessions, Borg scale and HRV was monitored (rest, exercise and recovery) for further analysis with the RMSSD-Slope. The RMSSD-Slope value in the 80% intensity test was 0.97 (± 0.78), and in the Maximum Test it was 0.84 (± 0.36). Both tests show an R2 with Borg scale of 0.62 and 0.62 respectively. In the case of the R2 between the ETL and the RMSSD-Slope it was 0.04 and 0.14 respectively. The recovery slope of the RMSSD is a good ITL assessment tool in physically active women but not athletes

Riesgo de recurrencia tras retirada de la anticoagulación en pacientes con enfermedad tromboembólica venosa no provocada: validación externa del nomograma de Viena y del modelo predictivo DASH / Risk Of Recurrence After Withdrawal Of Anticoagulation In Patients With Unprovoked Venous Thromboembolism: External Validation Of The Vienna Nomogram And The Dash Prediction Score

Introducción: Las escalas predictivas de recurrencias de ETV son útiles para decidir la duración del tratamiento anticoagulante. Aunque hay varias escalas, desconocemos la aplicabilidad de las mismas en nuestro medio. Por ello nos planteamos validar el modelo predictivo DASH y el nomograma de Viena a 12 meses. Métodos: Estudio retrospectivo de pacientes consecutivos no seleccionados con ETV no provocada desde 2006 hasta 2014. Comparamos la capacidad de predecir recurrencias de ETV de la escala DASH y el nomograma de Viena. La validación se realizó estratificando a los pacientes como de bajo o alto riesgo, según cada escala (discriminación) y comparando las recurrencias observadas frente a las esperadas (calibración). Resultados: De 353 pacientes evaluados, se analizaron 195, con una edad media de 53,5+/-19 años. Hubo 21 recurrencias a 1 año (10,8%, IC95%: 6,8-16%). Según la escala DASH, fueron catalogados de bajo riesgo el 42%, observando ETV recurrente en el grupo de bajo fue del 4,9% (IC95%: 1,3-12%) vs. el grupo de alto riesgo en que fue del 15% (IC95%: 9-23%) (p < 0,05). Según el nomograma de Viena, fueron catalogados de bajo riesgo el 30%, observando ETV recurrente en el grupo de bajo vs. alto riesgo en el 4,2% (IC95%: 0,5-14%) vs. 16,2% (IC95%: 9,9-24,4%) (p < 0,05). Conclusiones: Nuestro estudio valida la escala DASH y el nomograma de Viena en nuestra población. El modelo predictivo DASH sería el más aconsejable, tanto por su sencillez como por la capacidad de identificar a más pacientes de bajo riesgo frente al nomograma de Viena (42% vs. 30%)

Introduction: Scales for predicting venous thromboembolism (VTE) recurrence are useful for deciding the duration of the anticoagulant treatment. Although there are several scales, the most appropriate for our setting has not been identified. For this reason, we aimed to validate the DASH prediction score and the Vienna nomogram at 12 months. Methods: This was a retrospective study of unselected consecutive VTE patients seen between 2006 and 2014. We compared the ability of the DASH score and the Vienna nomogram to predict recurrences of VTE. The validation was performed by stratifying patients as low-risk or high-risk, according to each scale (discrimination) and comparing the observed recurrence with the expected rate (calibration). Results: Of 353 patients evaluated, 195 were analyzed, with an average age of 53.5 ± 19 years. There were 21 recurrences in 1 year (10.8%, 95% CI: 6.8%-16%). According to the DASH score, 42% were classified as low risk, and the rate of VTE recurrence in this group was 4.9% (95% CI: 1.3%-12%) vs. the high-risk group that was 15% (95% CI: 9%-23%) (p <.05). According to the Vienna nomogram, 30% were classified as low risk, and the rate of VTE recurrence in the low risk group vs. the high risk group was 4.2% (95% CI:0.5%-14%) vs. 16.2% (95% CI: 9.9%-24.4%) (p <.05). Conclusions: Our study validates the DASH score and the Vienna nomogram in our population. The DASH prediction score may be the most advisable, both because of its simplicity and its ability to identify more low-risk patients than the Vienna nomogram (42% vs. 30%)