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1.
World J Surg Oncol ; 19(1): 204, 2021 Jul 08.
Artigo em Inglês | MEDLINE | ID: mdl-34238303

RESUMO

BACKGROUND: Postoperative infectious complications (ICs) after surgery for colorectal cancer (CRC) increase in-hospital deaths and decrease long-term survival. However, the methodology for IC preoperative and intraoperative risk assessment has not yet been established. We aimed to construct a risk model for IC after surgery for CRC. METHODS: Between January 2016 and June 2020, a total of 593 patients who underwent curative surgery for CRC in Chengdu Second People's Hospital were enrolled. Preoperative and intraoperative factors were obtained retrospectively. The least absolute shrinkage and selection operator (LASSO) method was used to screen out risk factors for IC. Then, based on the results of LASSO regression analysis, multivariable logistic regression analysis was performed to establish the prediction model. Bootstraps with 300 resamples were performed for internal validation. The performance of the model was evaluated with its calibration and discrimination. The clinical usefulness was assessed by decision curve analysis (DCA). RESULTS: A total of 95 (16.0%) patients developed ICs after surgery for CRC. Chronic pulmonary diseases, diabetes mellitus, preoperative and/or intraoperative blood transfusion, and longer operation time were independent risk factors for IC. A prediction model was constructed based on these factors. The concordance index (C-index) of the model was 0.761. The calibration curve of the model suggested great agreement. DCA showed that the model was clinically useful. CONCLUSION: Several risk factors for IC after surgery for CRC were identified. A prediction model generated by these risk factors may help in identifying patients who may benefit from perioperative optimization.


Assuntos
Neoplasias Colorretais , Nomogramas , China/epidemiologia , Neoplasias Colorretais/cirurgia , Humanos , Prognóstico , Estudos Retrospectivos
2.
Zhongguo Yi Xue Ke Xue Yuan Xue Bao ; 43(3): 322-327, 2021 Jun 30.
Artigo em Chinês | MEDLINE | ID: mdl-34238406

RESUMO

Objective To establish a prediction model for the short-term efficacy of percutaneous ultrasound-guided radiofrequency ablation(RFA)in the treatment of papillary thyroid microcarcinoma(PTMC). Methods We retrospectively analyzed the preoperative and follow-up data of 159 patients with PTMC who underwent percutaneous ultrasound-guided RFA treatment in the Department of Ultrasound,the First Medical Center of Chinese PLA General Hospital from January to December in 2018.The association with 12-month tumor status(end event)was evaluated by multivariate logistic regression model.A nomogram was built to predict the risk of tumors which did not disappear completely within 12 months after RFA. Results We found that gender(P=0.017),age(P=0.047),and calcification(P=0.049)were the strongest predictors for establishing the model.The tumor maximum diameter and RFA energy were the secondary relevant factors for establishing the model.The constructed model showed good performance in both training cohort(AUC=0.762)and validation cohort(AUC=0.740). Conclusion A quantitative model was established for predicting the tumor status within one year after treatment of PTMC by RFA,which can accurately predict the short-term efficacy of RFA and provide a clinical basis for explaining the recovery results of patients.


Assuntos
Carcinoma Papilar , Ablação por Radiofrequência , Neoplasias da Glândula Tireoide , Carcinoma Papilar/cirurgia , Humanos , Nomogramas , Estudos Retrospectivos , Neoplasias da Glândula Tireoide/cirurgia , Resultado do Tratamento
3.
Medicine (Baltimore) ; 100(27): e26347, 2021 Jul 09.
Artigo em Inglês | MEDLINE | ID: mdl-34232169

RESUMO

ABSTRACT: More attention has been placed on nonfunctioning pancreatic neuroendocrine tumors due to the increase in its incidence in recent years. Whether tumor resection at the primary site of metastatic NFpNET is effective remains controversial. Moreover, clinicians need a more precise prognostic tool to estimate the survival of these patients.Patients with metastatic NFpNET were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Significant prognostic factors were identified using a multivariate Cox regression model and included in the nomogram. Coarsened exact matching analysis was used to balance the clinical variables between the non-surgical and surgical groups in our study.A total of 1464 patients with metastatic nonfunctioning pancreatic neuroendocrine tumors (NFpNETs) were included in our cohort. Multivariate analysis identified age, sex, tumor size, differentiated grade, lymph node metastases, resection of primary tumors, and marital status as independent predictors of metastatic NFpNET. The nomogram showed excellent accuracy in predicting 1-, 3-, and 5-year overall survival, with a C-index of 0.812. The calibration curve revealed good consistency between the predicted and actual survival.Coarsened exact matching analysis using SEER data indicated the survival advantages of resection of primary tumors. Our study is the first to build a nomogram model for patients with metastatic NFpNETs. This predictive tool can help clinicians identify high-risk patients and more accurately assess patient survival times.


Assuntos
Estadiamento de Neoplasias , Nomogramas , Neoplasias Pancreáticas/mortalidade , Programa de SEER , China/epidemiologia , Gerenciamento de Dados , Feminino , Seguimentos , Humanos , Masculino , Pessoa de Meia-Idade , Neoplasias Pancreáticas/diagnóstico , Neoplasias Pancreáticas/secundário , Prognóstico , Estudos Prospectivos , Taxa de Sobrevida/tendências
4.
Crit Care ; 25(1): 234, 2021 07 03.
Artigo em Inglês | MEDLINE | ID: mdl-34217339

RESUMO

BACKGROUND: The coronavirus disease 2019 (COVID-19) has induced a worldwide epidemiological event with a high infectivity and mortality. However, the predicting biomarkers and their potential mechanism in the progression of COVID-19 are not well known. OBJECTIVE: The aim of this study is to identify the candidate predictors of COVID-19 and investigate their underlying mechanism. METHODS: The retrospective study was conducted to identify the potential laboratory indicators with prognostic values of COVID-19 disease. Then, the prognostic nomogram was constructed to predict the overall survival of COVID-19 patients. Additionally, the scRNA-seq data of BALF and PBMCs from COVID-19 patients were downloaded to investigate the underlying mechanism of the most important prognostic indicators in lungs and peripherals, respectively. RESULTS: In total, 304 hospitalized adult COVID-19 patients in Wuhan Jinyintan Hospital were included in the retrospective study. CEA was the only laboratory indicator with significant difference in the univariate (P < 0.001) and multivariate analysis (P = 0.020). The scRNA-seq data of BALF and PBMCs from COVID-19 patients were downloaded to investigate the underlying mechanism of CEA in lungs and peripherals, respectively. The results revealed the potential roles of CEA were significantly distributed in type II pneumocytes of BALF and developing neutrophils of PBMCs, participating in the progression of COVID-19 by regulating the cell-cell communication. CONCLUSION: This study identifies the prognostic roles of CEA in COVID-19 patients and implies the potential roles of CEACAM8-CEACAM6 in the progression of COVID-19 by regulating the cell-cell communication of developing neutrophils and type II pneumocyte.


Assuntos
COVID-19/metabolismo , Antígeno Carcinoembrionário/metabolismo , Pneumonia Viral/metabolismo , Adulto , Idoso , Biomarcadores/metabolismo , Líquido da Lavagem Broncoalveolar/química , COVID-19/mortalidade , Comunicação Celular , China/epidemiologia , Progressão da Doença , Hospitalização , Humanos , Masculino , Pessoa de Meia-Idade , Neutrófilos/metabolismo , Nomogramas , Pneumonia Viral/mortalidade , Pneumonia Viral/virologia , Valor Preditivo dos Testes , Prognóstico , Estudos Retrospectivos , SARS-CoV-2 , Análise de Sobrevida
5.
Anticancer Res ; 41(7): 3657-3665, 2021 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-34230164

RESUMO

BACKGROUND/AIM: We attempted to stratify prognosis using the modified Journal of Hepato-Biliary-Pancreatic Sciences (mJHBPS) nomogram upon identification of colorectal liver metastasis (CRLM) and to investigate which strategy is better, surgery first (SF) or chemotherapy first (CF), in each risk group. PATIENTS AND METHODS: A total of 137 patients with CRLM who underwent resection of the primary tumor were included. Patients with brain, bone, or perihilar lymph node metastases were excluded. Patients were scored using the mJHBPS nomogram upon identification of CRLM. Prognosis was investigated using event-free survival (EFS) and overall survival (OS). RESULTS: The nomogram allowed stratification of patients using EFS and OS: low-risk (0-6 score, n=38), medium-risk (7-11 score, n=42), and high-risk (12≥ score, n=57). In the low-risk group, the EFS and OS of the CF group were significantly poorer than those of the SF group (p=0.019 and p=0.014, respectively). CF was an independent prognostic factor for both EFS and OS. CONCLUSION: The mJHBPS nomogram can stratify CRLM patients with sufficient differences in EFS and OS. SF was recommended for patients in the low-risk group.


Assuntos
Neoplasias Colorretais/patologia , Neoplasias Colorretais/terapia , Neoplasias Hepáticas/patologia , Neoplasias Hepáticas/terapia , Fígado/patologia , Idoso , Feminino , Humanos , Metástase Linfática/patologia , Masculino , Nomogramas , Pâncreas/patologia , Prognóstico , Intervalo Livre de Progressão , Estudos Retrospectivos
6.
BMC Neurol ; 21(1): 271, 2021 Jul 07.
Artigo em Inglês | MEDLINE | ID: mdl-34233656

RESUMO

BACKGROUND: Dementia is one of the greatest global health and social care challenges of the twenty-first century. The etiology and pathogenesis of Alzheimer's disease (AD) as the most common type of dementia remain unknown. In this study, a simple nomogram was drawn to predict the risk of AD in the elderly population. METHODS: Nine variables affecting the risk of AD were obtained from 1099 elderly people through clinical data and questionnaires. Least Absolute Shrinkage Selection Operator (LASSO) regression analysis was used to select the best predictor variables, and multivariate logistic regression analysis was used to construct the prediction model. In this study, a graphic tool including 9 predictor variables (nomogram-see precise definition in the text) was drawn to predict the risk of AD in the elderly population. In addition, calibration diagram, receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to verify the model. RESULTS: Six predictors namely sex, age, economic status, health status, lifestyle and genetic risk were identified by LASSO regression analysis of nine variables (body mass index, marital status and education level were excluded). The area under the ROC curve in the training set was 0.822, while that in the validation set was 0.801, suggesting that the model built with these 6 predictors showed moderate predictive ability. The DCA curve indicated that a nomogram could be applied clinically if the risk threshold was between 30 and 40% (30 to 42% in the validation set). CONCLUSION: The inclusion of sex, age, economic status, health status, lifestyle and genetic risk into the risk prediction nomogram could improve the ability of the prediction model to predict AD risk in the elderly patients.


Assuntos
Doença de Alzheimer/epidemiologia , Nomogramas , Idoso , Idoso de 80 Anos ou mais , Humanos , Curva ROC , Medição de Risco , Fatores de Risco
7.
World J Surg Oncol ; 19(1): 219, 2021 Jul 20.
Artigo em Inglês | MEDLINE | ID: mdl-34284774

RESUMO

BACKGROUND: Gastric cancer (GC) commonly relates to dismal prognosis and lacks efficient biomarkers. This study aimed to establish an antioxidant-related gene signature and a comprehensive nomogram to explore novel biomarkers and predict GC prognosis. METHODS: Clinical and expression data of GC patients were extracted from The Cancer Genome Atlas database. Univariate and multivariate Cox analyses were utilized to construct a score-based gene signature and survival analyses were conducted between high- and low-risk groups. Furthermore, we established a prognostic nomogram integrating clinical variables and antioxidant-related gene signature. Its predictive ability was validated by Harrell' concordance index and calibration curves and an independent internal cohort verified the consistency of the antioxidant gene signature-based nomogram. RESULTS: Four antioxidant-related genes (CHAC1, GGT5, GPX8, and PXDN) were significantly associated with overall survival of GC patients but only two genes, CHAC1 (HR = 0.803, P < 0.05) and GPX8 (HR = 1.358, P < 0.05), were confirmed as independent factors. A score-based signature was constructed and could act as an independent prognosis predictor (P < 0.05). Patients with lower scores showed significantly better prognosis (P < 0.05). Comprehensive nomogram combining the antioxidant-related gene signature and clinical parameters (age, gender, grade, and stage) was established and effectively predicted overall survival of GC patients [3-year survival AUC = 0.680, C index = 0.665 (95% CI 0.614-0.716)]. The independent internal validation cohort verified the reliability and good consistency of the model [3-year survival AUC = 0.703, C index = 0.706 (95% CI 0.612-0.800)]. CONCLUSIONS: Innovative antioxidant-related gene signature and nomogram performed well in assessing GC prognoses. This study enlightened further investigation of antioxidant system and provided novel tools for GC patient management.


Assuntos
Neoplasias Gástricas , Antioxidantes , Humanos , Nomogramas , Peroxidases , Prognóstico , Reprodutibilidade dos Testes , Neoplasias Gástricas/genética
8.
Medicine (Baltimore) ; 100(23): e26021, 2021 Jun 11.
Artigo em Inglês | MEDLINE | ID: mdl-34114989

RESUMO

ABSTRACT: The present study aimed to develop nomograms to predict survival in patients with chondroblastic osteosarcoma (COS).An analysis was conducted of 320 cases of COS collected from the surveillance, epidemiology, and end results (SEER) database between 2004 and 2015. Independent prognostic factors were screened using univariate and multivariate Cox analyses. Subsequently, nomograms were established to predict the patients' cancer-specific survival (CSS) and overall survival (OS) rates. The prediction accuracy and discriminative ability of the nomograms were examined using calibration curves and the concordance index (C-index).As revealed in the univariate and multivariate Cox regression analysis, age, tumor size, the primary site, the presence of metastasis, a history of having undergone surgery, and a history of having received radiotherapy were found to be independent prognostic factors associated with survival in patients with COS (all P < .05). Furthermore, age >39 years, the presence of distant metastasis, no history of having undergone any surgery, and tumor size >103 mm were found to be associated with poor prognosis in patients, while the primary site of the mandible and no history of having undergone radiotherapy showed associations with a more favorable prognosis in patients. Next, nomograms were constructed to predict the OS and CSS in patients with COS.We constructed nomograms that can provide accurate survival predictions in patients with chondroblastic osteosarcoma. These nomograms can help surgeons customize the treatment strategies for patients with chondroblastic osteosarcoma.


Assuntos
Condroblastoma , Nomogramas , Osteossarcoma , Risco Ajustado/métodos , Programa de SEER/estatística & dados numéricos , Fatores Etários , Condroblastoma/mortalidade , Condroblastoma/patologia , Condroblastoma/terapia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Metástase Neoplásica , Estadiamento de Neoplasias , Osteossarcoma/mortalidade , Osteossarcoma/patologia , Osteossarcoma/terapia , Valor Preditivo dos Testes , Prognóstico , Radioterapia/métodos , Radioterapia/estatística & dados numéricos , Procedimentos Cirúrgicos Operatórios/métodos , Procedimentos Cirúrgicos Operatórios/estatística & dados numéricos , Análise de Sobrevida , Carga Tumoral
9.
BMC Surg ; 21(1): 296, 2021 Jun 17.
Artigo em Inglês | MEDLINE | ID: mdl-34140016

RESUMO

BACKGROUND: Laparoscopic anterior resection with trans-rectal specimen extraction (NOSES) has been demonstrated as a safe and effective technique in appropriate patients with upper rectal cancer (RC). However, improper selection of RC candidates for NOSES may lead to potential surgical and oncological unsafety as well as complications such as bacteria contamination and anastomotic leak. Unfortunately, no tools are available for evaluating the risk and excluding improper cases before surgery. This study aims to estimate its clinical relevancy and to investigate independent clinical-pathological predictors for identifying candidates for NOSES in patients with upper RC and to develop a validated scoring nomogram to facilitate clinical decision making. METHODS: The study was performed at Shanghai East hospital, a tertiary medical center and teaching hospital. 111 eligible patients with upper RC who underwent elective laparoscopic anterior resection between February and October of 2017 were included in the final analysis. Univariate and multivariate analyses were performed to compare characteristics between the two surgical techniques. Odds ratios (OR) were determined by logistic regression analyses to identify and quantify the clinical relevancy and ability of predictors for identifying NOSES candidate. The nomogram was constructed and characterized by c-index, calibration, bootstrapping validation, ROC curve analysis, and decision curve analysis. RESULTS: Upper RC patients with successful NOSES tended to be featured with female gender, negative preoperative CEA/CA19-9, decreased mesorectum length (MRL), ratio of diameter (ROD) and ratio of area (ROA) values, while no significant statistical correlations were observed with age, body mass index (BMI), tumor location, and tumor-related biological characteristics (ie., vascular invasion, lymph node count, TNM stages). Furthermore, the two techniques exhibited comparably low incidence of perioperative complications and achieved similar functional results under the standard procedures. The nomogram incorporating three independent preoperative predictors including gender, CEA status and ROD showed a high c-index of 0.814 and considerable reliability, accuracy and clinical net benefit. CONCLUSIONS: NOSES for patients with upper RC is multifactorial; while it is a safe and efficient technique if used properly. The nomogram is useful for patient evaluation in the future.


Assuntos
Laparoscopia , Neoplasias Retais , China , Estudos de Viabilidade , Feminino , Humanos , Nomogramas , Neoplasias Retais/cirurgia , Reprodutibilidade dos Testes , Estudos Retrospectivos
10.
J Biomed Nanotechnol ; 17(6): 1109-1122, 2021 Jun 01.
Artigo em Inglês | MEDLINE | ID: mdl-34167625

RESUMO

Sub-solid nodules (SSN) are common radiographic findings. Due to possibility of malignancy, further evaluation is urgentlyneeded for prevention and management of lung cancer (LC). This current study enrolled patients with SSN, including LC, benign nodules (BN), and healthy individuals as a control, to discover small extracellular vesicles (sEVs) differentially expressed miRNAs (DEMs) as biomarker by next-generation sequencing (NGS) and validation by RT-qPCR. Through cross-scale integration of validated small-molecule and macro-imaging, the prediction model was developed by logistic algorithms and further interpreted into an easy-to-use Nomogram by Cox-proportional hazards modeling. Present study has discovered various sEVs DEMs and sEVs-miR-424-5p that were selected and validated as novel potential biomarkers for cancerous nodule, namely LC. Furthermore, the 10 radiomics signs and 4 clinical features of SSN were merged with sEVs-miR-424-5p and proceeded in multivariate logistic regression analysis to develop the cross-scale integrated modeling, which yielded a significantly higher area under the curve (AUC). Finally, visualization of an easy-to-use nomogram was invented to potentially predict suspected SSN. sEVs-miR-424-5p could be a novel biomarker for distinguishing SSN from LC and BN populations. Its association with cross-scale fusion of radiomics-clinical features will provide great potential to be an errorless prediction of malignant SSN.


Assuntos
Vesículas Extracelulares , Neoplasias Pulmonares , Biomarcadores , Humanos , Neoplasias Pulmonares/diagnóstico por imagem , Nomogramas , Tomografia Computadorizada por Raios X
11.
BMC Infect Dis ; 21(1): 608, 2021 Jun 25.
Artigo em Inglês | MEDLINE | ID: mdl-34171991

RESUMO

BACKGROUND: Convenient and precise assessment of the severity in coronavirus disease 2019 (COVID-19) contributes to the timely patient treatment and prognosis improvement. We aimed to evaluate the ability of CT-based radiomics nomogram in discriminating the severity of patients with COVID-19 Pneumonia. METHODS: A total of 150 patients (training cohort n = 105; test cohort n = 45) with COVID-19 confirmed by reverse transcription polymerase chain reaction (RT-PCR) test were enrolled. Two feature selection methods, Max-Relevance and Min-Redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO), were used to extract features from CT images and construct model. A total of 30 radiomic features were finally retained. Rad-score was calculated by summing the selected features weighted by their coefficients. The radiomics nomogram incorporating clinical-radiological features was eventually constructed by multivariate regression analysis. Nomogram, calibration, and decision-curve analysis were all assessed. RESULTS: In both cohorts, 40 patients with COVID-19 pneumonia were severe and 110 patients were non-severe. By combining the 30 radiomic features extracted from CT images, the radiomics signature showed high discrimination between severe and non-severe patients in the training set [Area Under the Curve (AUC), 0.857; 95% confidence interval (CI), 0.775-0.918] and the test set (AUC, 0.867; 95% CI, 0.732-949). The final combined model that integrated age, comorbidity, CT scores, number of lesions, ground glass opacity (GGO) with consolidation, and radiomics signature, improved the AUC to 0.952 in the training cohort and 0.98 in the test cohort. The nomogram based on the combined model similarly exhibited excellent discrimination performance in both training and test cohorts. CONCLUSIONS: The developed model based on a radiomics signature derived from CT images can be a reliable marker for discriminating the severity of COVID-19 pneumonia.


Assuntos
COVID-19/diagnóstico por imagem , COVID-19/diagnóstico , Nomogramas , Tomografia Computadorizada por Raios X/métodos , Adulto , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Prognóstico , SARS-CoV-2/patogenicidade
12.
Abdom Radiol (NY) ; 46(6): 2384-2392, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-34086094

RESUMO

PURPOSE: To develop and validate a radiomic nomogram based on arterial phase of CT to discriminate the primary ovarian cancers (POCs) and secondary ovarian cancers (SOCs). METHODS: A total of 110 ovarian cancer patients in our hospital were reviewed from January 2010 to December 2018. Radiomic features based on the arterial phase of CT were extracted by Artificial Intelligence Kit software (A.K. software). The least absolute shrinkage and selection operation regression (LASSO) was employed to select features and construct the radiomics score (Rad-score) for further radiomics signature calculation. Multivariable logistic regression analysis was used to develop the predicting model. The predictive nomogram model was composed of rad-score and clinical data. Nomogram discrimination and calibration were evaluated. RESULTS: Two radiomic features were selected to build the radiomics signature. The radiomics nomogram that incorporated 2 radiomics signature and 2 clinical factors (CA125 and CEA) showed good discrimination in training cohort (AUC 0.854), yielding the sensitivity of 78.8% and specificity of 90.7%, which outperformed the prediction model based on radiomics signature or clinical data alone. A visualized differential nomogram based on the radiomic score, CEA, and CA125 level was established. The calibration curve demonstrated the clinical usefulness of the proposed nomogram. CONCLUSION: The presented nomogram, which incorporated radiomic features of arterial phase of CT with clinical features, could be useful for differentiating the primary and secondary ovarian cancers.


Assuntos
Nomogramas , Neoplasias Ovarianas , Inteligência Artificial , Diagnóstico Diferencial , Feminino , Humanos , Neoplasias Ovarianas/diagnóstico por imagem , Tomografia Computadorizada por Raios X
13.
Dis Markers ; 2021: 5598824, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34158873

RESUMO

Assessing the length of hospital stay (LOS) in patients with coronavirus disease 2019 (COVID-19) pneumonia is helpful in optimizing the use efficiency of hospital beds and medical resources and relieving medical resource shortages. This retrospective cohort study of 97 patients was conducted at Beijing You'An Hospital between January 21, 2020, and March 21, 2020. A multivariate Cox proportional hazards regression based on the smallest Akaike information criterion value was used to select demographic and clinical variables to construct a nomogram. Discrimination, area under the receiver operating characteristic curve (AUC), calibration, and Kaplan-Meier curves with the log-rank test were used to assess the nomogram model. The median LOS was 13 days (interquartile range [IQR]: 10-18). Age, alanine aminotransferase, pneumonia, platelet count, and PF ratio (PaO2/FiO2) were included in the final model. The C-index of the nomogram was 0.76 (95%confidence interval [CI] = 0.69-0.83), and the AUC was 0.88 (95%CI = 0.82-0.95). The adjusted C-index was 0.75 (95%CI = 0.67-0.82) and adjusted AUC 0.86 (95%CI = 0.73-0.95), both after 1000 bootstrap cross internal validations. A Brier score of 0.11 (95%CI = 0.07-0.15) and adjusted Brier score of 0.130 (95%CI = 0.07-0.20) for the calibration curve showed good agreement. The AUC values for the nomogram at LOS of 10, 20, and 30 days were 0.79 (95%CI = 0.69-0.89), 0.89 (95%CI = 0.83-0.96), and 0.96 (95%CI = 0.92-1.00), respectively, and the high fit score of the nomogram model indicated a high probability of hospital stay. These results confirmed that the nomogram model accurately predicted the LOS of patients with COVID-19. We developed and validated a nomogram that incorporated five independent predictors of LOS. If validated in a future large cohort study, the model may help to optimize discharge strategies and, thus, shorten LOS in patients with COVID-19.


Assuntos
COVID-19/terapia , Tempo de Internação , Nomogramas , SARS-CoV-2 , Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Modelos de Riscos Proporcionais , Estudos Retrospectivos
15.
Front Immunol ; 12: 577517, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34084158

RESUMO

Background: Extracellular traps (ETs) and tumor-infiltrating immune cells can contribute to disease progression. The clinical significance of tumor-infiltrating neutrophils and macrophages and related extracellular traps in pancreatic neuroendocrine tumors (pNETs) has not been fully elucidated. This study aimed to explore the prognostic value of tumor infiltration and ET formation by neutrophils and macrophages in pNETs. Methods: A total of 135 patients with radical resection of nonfunctional pNETs were analyzed retrospectively. Immunohistochemistry and immunofluorescence were utilized to stain tumor tissue sections. The recurrence-free survival (RFS) of subgroups determined by Kaplan-Meier analysis was compared with the log-rank test. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. A nomogram was established to predict 3-year RFS. Results: Patients with high tumor-infiltrating neutrophils or macrophages or positive expression of neutrophils ETs or macrophage ETs displayed worse RFS (all p<0.05). Moreover, univariate and multivariate Cox regression analyses showed that neutrophil and macrophage infiltration and ETs were independent prognostic factors for RFS (all p<0.05). A combined parameter including WHO grade, TNM stage, tumor-infiltrating neutrophils and macrophages, and neutrophil and macrophage ETs had the highest C-index (0.866) and lowest Akaike information criteria (326.557). The calibration plot of nomogram composed of the combined parameter exhibited excellent prognostic values for 3-year RFS. Conclusions: Infiltration and ETs by neutrophils and macrophages can be used as biological indicators of patient prognosis, suggesting the treatment potential for targeting those in nonfunctional pNETs.


Assuntos
Armadilhas Extracelulares/imunologia , Macrófagos/imunologia , Tumores Neuroendócrinos/imunologia , Infiltração de Neutrófilos/imunologia , Neoplasias Pancreáticas/imunologia , Adulto , Feminino , Humanos , Estimativa de Kaplan-Meier , Macrófagos/patologia , Masculino , Pessoa de Meia-Idade , Recidiva Local de Neoplasia , Tumores Neuroendócrinos/patologia , Tumores Neuroendócrinos/cirurgia , Nomogramas , Neoplasias Pancreáticas/patologia , Neoplasias Pancreáticas/cirurgia , Prognóstico , Estudos Retrospectivos
16.
Medicine (Baltimore) ; 100(22): e26219, 2021 Jun 04.
Artigo em Inglês | MEDLINE | ID: mdl-34087900

RESUMO

BACKGROUND: Autophagy is closely related to skin cutaneous melanoma (SKCM), but the mechanism involved is unclear. Therefore, exploration of the role of autophagy-related genes (ARGs) in SKCM is necessary. MATERIALS AND METHODS: Differential expression autophagy-related genes (DEARGs) were first analysed. Univariate and multivariate Cox regression analyses were used to evaluate the expression of DEARGs and prognosis of SKCM. Further, the expression levels of prognosis-related DEARGs were verified by immunohistochemical (IHC) staining. Finally, gene set enrichment analysis (GSEA) was used to explore the underlying molecular mechanisms of SKCM. RESULTS: Five ARGs (APOL1, BIRC5, EGFR, TP63, and SPNS1) were positively correlated with the prognosis of SKCM. IHC verified the results of the differential expression of these 5 ARGs in the bioinformatics analysis. According to the receiver operating characteristic curve, the signature had a good performance at predicting overall survival in SKCM. The signature could classify SKCM patients into high-risk or low-risk groups according to distinct overall survival. The nomogram confirmed that the risk score has a particularly large impact on the prognosis of SKCM. Calibration plot displayed excellent agreement between nomogram predictions and actual observations. Principal component analysis indicated that patients in the high-risk group could be distinguished from those in low-risk group. Results of GSEA indicated that the low-risk group is enriched with aggressiveness-related pathways such as phosphatidylinositol-3-kinase/protein kinase B and mitogen-activated protein kinase signalling pathways. CONCLUSION: Our study identified a 5-gene signature. It revealed the mechanisms of autophagy that lead to the progression of SKCM and established a prognostic nomogram that can predict overall survival of patients with SKCM. The findings of this study provide novel insights into the relationship between ARGs and prognosis of SKCM.


Assuntos
Autofagia/genética , Biologia Computacional/métodos , Melanoma/genética , Neoplasias Cutâneas/patologia , Proteínas Adaptadoras de Transdução de Sinal/genética , Apolipoproteína L1/genética , Receptores ErbB/genética , Feminino , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica , Humanos , Masculino , Melanoma/mortalidade , Proteínas de Membrana/genética , Proteínas Quinases Ativadas por Mitógeno/metabolismo , Nomogramas , Fosfatidilinositol 3-Quinase/metabolismo , Prognóstico , Estudos Prospectivos , Proteínas Proto-Oncogênicas c-akt/metabolismo , Curva ROC , Fatores de Risco , Survivina/genética , Fatores de Transcrição/genética , Proteínas Supressoras de Tumor/genética
17.
Zhejiang Da Xue Xue Bao Yi Xue Ban ; 50(1): 81-89, 2021 02 25.
Artigo em Inglês | MEDLINE | ID: mdl-34117856

RESUMO

:To establish and verify a risk prediction nomogram for ipsilateral axillary lymph node metastasis in breast cancer stage T1 (mass ≤ 2 cm). :The clinicopathological data of 907 patients with T1 breast cancer who underwent surgical treatment from January 2010 to June 2015 were collected,including 573 cases from the Second Affiliated Hospital of Zhejiang University School of Medicine (modeling group) and 334 cases from Zhejiang University Lishui Hospital (verification group). The risk factors of ipsilateral axillary lymph node metastasis were analyzed by univariate and multivariate logistic regression. The influencing factors were used to establish a nomogram for predicting ipsilateral axillary lymph nodes metastasis in T1 breast cancer. The model calibration,predictive ability and clinical benefit in the modeling group and the verification group were analyzed by C index,receiver operating characteristic curve,calibration curve and decision curve analysis (DCA) curve,respectively. :Univariate analysis showed that lymph node metastasis was related with primary tumor size,vascular tumor thrombus,Ki-67,histopathological grade,and molecular type (<0.05 or <0.01). Multivariate logistic regression analysis showed that the primary tumor > vascular tumor thrombus,Ki-67 positive,estrogen receptor (ER) positive,and histopathological grade 2-3 were independent risk factors of axillary lymph node metastasis (<0.05 or <0.01). Based on the independent risk factors,a nomogram prediction model was established. The C indexes of the model group and the validation group were 0.739 (95%:0.693-0.785) and 0.736 (95%:0.678-0.793),respectively. The calibration curve and DCA curve of the modeling group and the verification group indicated that the model was consistent and had good clinical benefit. :Primary tumor size,histopathological grade,vascular tumor thrombus,Ki-67,and ER status are predictors of ipsilateral axillary lymph node metastasis in T1 breast cancer. The established prediction nomogram can effectively predict the risk of ipsilateral axillary lymph node metastasis in T1 breast cancer,which can be used as a reference for individualized axillary management.


Assuntos
Neoplasias da Mama , Nomogramas , Axila , Feminino , Humanos , Linfonodos , Metástase Linfática , Estudos Retrospectivos
18.
Ann Palliat Med ; 10(6): 6208-6219, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-34154348

RESUMO

BACKGROUND: This study aimed to identify risk factors that were associated with mandatory intensive care unit (ICU) admission after gastrectomy for gastric cancer. We then employed these risk factors to construct and validate a nomogram for predicting mandatory ICU admission after gastrectomy, which may identify those who require ICU indeed and improve ICU utilization. METHODS: A number of 999 gastric cancer patients undergoing gastrectomy from January 2010 to June 2019 were included in the retrospective study. Forty-three patients were classified into mandatory ICU admission groups, and the remaining 956 patients were allocated into the no need for ICU admission group. The candidate variables, including patient demographic characteristics, preoperative laboratory tests and surgical variables, were compared between the two groups. We then carried out univariate and multivariate logistic regression analyses to find out risk factors for mandatory ICU admission. In order to develop the predictive model, we used Akaike information criterion (AIC) to select risk factors via a step-down backward process from the multivariate regression model. RESULTS: A number of risk factors for mandatory ICU admission were identified and subsequently used to build the nomogram: age [odds ratio (OR), 1.03; 95% CI, 1.00-1.07; P=0.031], ASA status (III-IV vs. I-II: OR,1.74; 95% CI, 0.88-3.46; P=0.114), tumor size (OR, 1.28; 95% CI, 1.08-1.51; P=0.004), estimated blood loss (OR, 1.001; 95% CI, 1.000-1.001; P=0.082) as well as intraoperative transfusion (Yes vs. No: OR, 3.82; 95% CI, 1.87-7.82; P<0.001). C-index of the nomogram was 0.800, indicating good discrimination. Both Calibration curve and Hosmer-Lemeshow goodness-of-fit tests (P=0.128) showed that there was a high degree of agreement between the prediction and actual outcome. CONCLUSIONS: A nomogram to predict mandatory ICU admission after gastrectomy for gastric cancer was constructed and validated. Clinicians could apply this predictive model to improve usage of limited ICU resources effectively.


Assuntos
Nomogramas , Neoplasias Gástricas , Gastrectomia , Humanos , Unidades de Terapia Intensiva , Estudos Retrospectivos , Neoplasias Gástricas/cirurgia
19.
Medicine (Baltimore) ; 100(26): e26415, 2021 Jul 02.
Artigo em Inglês | MEDLINE | ID: mdl-34190160

RESUMO

ABSTRACT: Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, and its pathogenesis is complicated and triggered by unbalanced diet, sedentary lifestyle, and genetic background. The aim of this study was to construct and validate a nomogram incorporated lifestyle habits for predicting NAFLD incidence.The overall cohort was divided into training set and test set as using computer-generated random numbers. We constructed the nomogram by multivariate logistic regression analysis in the training set. Thereafter, we validated this model by concordance index, the area under the receiver operating characteristic curve (ROC), net reclassification index, and a calibration curve in the test set. Additionally, we also evaluated the clinical usefulness of the nomogram by decision curve analysis.There were no statistically significant differences about characteristics between training cohort (n = 748) and test cohort (n = 320). Eleven features (age, sex, body mass index, drinking tea, physical exercise, energy, monounsaturated fatty acids, polyunsaturated fatty acids, hypertension, hyperlipidemia, diabetes) were incorporated to construct the nomogram, concordance index, the area under the ROC curve, net reclassification index were 0.801, 0.801, and 0.084, respectively, indicating the nomogram have good discrimination of predicting NAFLD incidence. Also, the calibration curve showed good consistency between nomogram prediction and actual probability. Moreover, the decision curve showed that when the threshold probability of an individual is within a range from approximately 0.5 to 0.8, this model provided more net benefit to predict NAFLD incidence risk than the current strategies.This nomogram can be regarded as a user-friendly tool for assessing the risk of NAFLD incidence, and thus help to facilitate management of NAFLD including lifestyle and medical interventions.


Assuntos
Estilo de Vida , Nomogramas , Hepatopatia Gordurosa não Alcoólica/epidemiologia , Medição de Risco/métodos , Adulto , Fatores Etários , Índice de Massa Corporal , Comorbidade , Dieta , Exercício Físico , Feminino , Humanos , Hiperlipidemias/epidemiologia , Hipertensão/epidemiologia , Incidência , Masculino , Pessoa de Meia-Idade , Obesidade/epidemiologia , Estudos Retrospectivos , Fatores Sexuais , Adulto Jovem
20.
Aging (Albany NY) ; 13(11): 15061-15077, 2021 06 03.
Artigo em Inglês | MEDLINE | ID: mdl-34081620

RESUMO

We developed and validated a nomogram to predict the risk of stroke in patients with rheumatoid arthritis (RA) in northern China. Out of six machine learning algorithms studied to improve diagnostic and prognostic accuracy of the prediction model, the logistic regression algorithm showed high performance in terms of calibration and decision curve analysis. The nomogram included stratifications of sex, age, systolic blood pressure, C-reactive protein, erythrocyte sedimentation rate, total cholesterol, and low-density lipoprotein cholesterol along with the history of traditional risk factors such as hypertensive, diabetes, atrial fibrillation, and coronary heart disease. The nomogram exhibited a high Hosmer-Lemeshow goodness-for-fit and good calibration (P > 0.05). The analysis, including the area under the receiver operating characteristic curve, the net reclassification index, the integrated discrimination improvement, and clinical use, showed that our prediction model was more accurate than the Framingham risk model in predicting stroke risk in RA patients. In conclusion, the nomogram can be used for individualized preoperative prediction of stroke risk in RA patients.


Assuntos
Artrite Reumatoide/complicações , Nomogramas , Acidente Vascular Cerebral/epidemiologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Calibragem , Estudos de Coortes , Feminino , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Modelos Biológicos , Reprodutibilidade dos Testes , Fatores de Risco , Adulto Jovem
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