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1.
BMC Med Imaging ; 20(1): 111, 2020 10 02.
Artigo em Inglês | MEDLINE | ID: mdl-33008329

RESUMO

BACKGROUND: To develop and validate a nomogram for early identification of severe coronavirus disease 2019 (COVID-19) based on initial clinical and CT characteristics. METHODS: The initial clinical and CT imaging data of 217 patients with COVID-19 were analyzed retrospectively from January to March 2020. Two hundred seventeen patients with 146 mild cases and 71 severe cases were randomly divided into training and validation cohorts. Independent risk factors were selected to construct the nomogram for predicting severe COVID-19. Nomogram performance in terms of discrimination and calibration ability was evaluated using the area under the curve (AUC), calibration curve, decision curve, clinical impact curve and risk chart. RESULTS: In the training cohort, the severity score of lung in the severe group (7, interquartile range [IQR]:5-9) was significantly higher than that of the mild group (4, IQR,2-5) (P < 0.001). Age, density, mosaic perfusion sign and severity score of lung were independent risk factors for severe COVID-19. The nomogram had a AUC of 0.929 (95% CI, 0.889-0.969), sensitivity of 84.0% and specificity of 86.3%, in the training cohort, and a AUC of 0.936 (95% CI, 0.867-1.000), sensitivity of 90.5% and specificity of 88.6% in the validation cohort. The calibration curve, decision curve, clinical impact curve and risk chart showed that nomogram had high accuracy and superior net benefit in predicting severe COVID-19. CONCLUSION: The nomogram incorporating initial clinical and CT characteristics may help to identify the severe patients with COVID-19 in the early stage.


Assuntos
Infecções por Coronavirus/diagnóstico por imagem , Pulmão/diagnóstico por imagem , Nomogramas , Pneumonia Viral/diagnóstico por imagem , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Área Sob a Curva , Criança , Diagnóstico Precoce , Humanos , Pessoa de Meia-Idade , Pandemias , Distribuição Aleatória , Estudos Retrospectivos , Sensibilidade e Especificidade , Índice de Gravidade de Doença , Tomografia Computadorizada por Raios X , Adulto Jovem
2.
Zhonghua Zhong Liu Za Zhi ; 42(8): 653-659, 2020 Aug 23.
Artigo em Chinês | MEDLINE | ID: mdl-32867457

RESUMO

Objective: To identify the risk factors of non-sentinel lymph node (nSLN) metastasis in breast cancer patients with 1~2 positive axillary sentinel lymph node (SLN) and construct an accurate prediction model. Methods: Retrospective chart review was performed in 917 breast cancer patients who underwent surgery treatment between 2002 and 2017 and pathologically confirmed 1-2 positive SLNs. According to the date of surgery, patients were divided into training group (497 cases) and validation group (420 cases). A nomogram was built to predict nSLN metastasis and the accuracy of the model was validated. Results: Among the 917 patients, 251 (27.4%) had nSLN metastasis. Univariate analysis showed tumor grade, lymphovascular invasion (LVI), extra-capsular extension (ECE), the number of positive and negative SLN and macro-metastasis of SLN were associated with nSLN metastasis (all P<0.05). Multivariate Logistic regression analysis showed the numbers of positive SLN, negative SLN and macro-metastasis of SLN were independent predictors of nSLN metastasis (all P<0.05). A nomogram was constructed based on the 6 factors. The area under the receiver operating characteristic curve was 0.718 for the training group and 0.742 for the validation group. Conclusion: We have developed a nomogram that uses 6 risk factors commonly available to accurately estimate the likelihood of nSLN metastasis for individual patient, which might be helpful for radiation oncologists to make a decision on regional nodal irradiation.


Assuntos
Neoplasias da Mama/patologia , Excisão de Linfonodo , Metástase Linfática/diagnóstico , Nomogramas , Biópsia de Linfonodo Sentinela , Linfonodo Sentinela/patologia , Axila , Humanos , Linfonodos/patologia , Estudos Retrospectivos
3.
Medicine (Baltimore) ; 99(38): e22191, 2020 Sep 18.
Artigo em Inglês | MEDLINE | ID: mdl-32957347

RESUMO

To investigate the role of previous cancer on overall survival in patients with bladder cancer (BCa) and to establish an effective prognostic tool for individualized overall survival prediction.A total of 78,660 patients diagnosed with BCa between 2000 and 2013 were selected from the Surveillance, Epidemiology, and End Results (SEER) database, among which 8915 patients had a history of other cancers. We compared the overall survival between patients with and without previous cancer after propensity score matching and we further established a nomogram for overall survival prediction.Univariate and multivariate Cox analyses were used to determine independent prognostic factors. The calibration curve and concordance index (C-index) were used to assess the accuracy of the nomogram. Cox proportional hazards models and Kaplan-Meier analysis were used to compare survival outcomes.BCa patients with previous cancer had worse overall survival compared with those without previous cancer (HR = 1.37; 95%CI = 1.32-1.42, P < .001). Cancers in lung prior to BCa had the most adverse impact on overall survival (HR = 2.35; 95%CI = 2.10-2.63; P < .001), and the minimal impact was located in prostate (HR = 1.16; 95%CI = 1.10-1.22; P < .001) for male and in gynecological (HR = 1.15; 95%CI = 1.02-1.30; P = .027) for female. The shorter interval time between 2 cancers and the higher stage of the previous cancer development, the higher risk of death. Age, race, sex, marital status, surgery, radiation, grade, stage, type of previous cancer as the independent prognostic factors were selected into the nomogram. The favorable calibration curve and C-index value (0.784, 95%CI = 0.782-0.786) indicated the nomogram could accurately predict the 1-, 3-, and 5-year overall survival rate of BCa patients.Previous cancer has a negative impact on the overall survival of BCa patients and requires more effective clinical management. The nomogram provides accurate survival prediction for BCa patients and might be helpful for clinical treatment selection and follow-up strategy adjustment.


Assuntos
Carcinoma de Células de Transição/mortalidade , Segunda Neoplasia Primária/mortalidade , Neoplasias da Bexiga Urinária/mortalidade , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Nomogramas , Programa de SEER
4.
Medicine (Baltimore) ; 99(38): e22200, 2020 Sep 18.
Artigo em Inglês | MEDLINE | ID: mdl-32957351

RESUMO

The central lymph nodes of the neck are the most common sites of papillary thyroid carcinoma (PTC) but cannot be easily diagnosed preoperatively. Prophylactic central lymph node dissection (CLND), especially contralateral CLND, is not recommended in various guidelines due to its high risk. The aim of our study was to establish an objective point score based on preoperative and intraoperative data to guide the selection of patients for contralateral CLND.We retrospectively evaluated 1085 consecutive patients with PTC treated by thyroidectomy for inclusion in this study (the training cohort). Variables of contralateral central lymph node macro-metastasis (CLNMM) were investigated using univariate and multivariate analyses; subsequently, nomograms were developed and then validated in an independent cohort of patients (n = 326, the validation cohort).Univariate and multivariate analyses indicated that preoperative fine needle aspiration-proven ipsilateral lateral lymph node metastasis (LNM) (odds ratio [OR] 4.888, 95% confidence interval [CI] 1.587-41.280, P < .001) and cases with frozen-section pretracheal LNM (OR 19.015, 95% CI 2.949-186.040, P < .001) or Delphian LNM (OR 4.494, 95% CI 1.503-54.128, P < .001) were the 3 risk factors for contralateral CLNMM. A receiver operating characteristic curve indicated a cutoff value of 1 for the frozen-section pretracheal LNM number or the Delphian LNM number as a predictor of contralateral central lymph node metastasis (CLNM). The nomogram was then generated according to the 3 risk factors and well validated in the external cohorts, and the intraoperative frozen-section results were highly consistent with the postoperative pathological results.The proposed nomogram based on the 3 factors showed a good prediction of contralateral CLNMM in PTC.


Assuntos
Excisão de Linfonodo , Linfonodos/patologia , Câncer Papilífero da Tireoide/patologia , Neoplasias da Glândula Tireoide/patologia , Adulto , Técnicas de Apoio para a Decisão , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Nomogramas , Curva ROC , Câncer Papilífero da Tireoide/cirurgia , Neoplasias da Glândula Tireoide/cirurgia
5.
Medicine (Baltimore) ; 99(35): e21996, 2020 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-32871952

RESUMO

It is of significance to evaluate central lymph node status in patients with papillary thyroid carcinoma (PTC), because it can decrease postoperative complications resulting from unnecessary prophylactic central lymph node dissection (CLND). Due to the low sensitivity and specificity of neck ultrasonography in the evaluation of central lymph node metastasis (CLNM), it is urgently required to find alternative biomarkers to predict CLNM in PTC patients, which is the main purpose of this study.RNA-sequencing datasets and clinical data of 506 patients with thyroid carcinoma from the Cancer Genome Atlas (TCGA) database were downloaded and analyzed to identify differentially expressed miRNAs (DEMs), which can independently predict CLNM in PTC. A nomogram predictive of CLNM was developed based on clinical characteristics and the identified miRNAs. Receiver operating characteristics curves were drawn to evaluate the predictive performance of the nomogram. Bioinformatics analyses, including target genes identification, functional enrichment analysis, and protein-protein interaction network, were performed to explore the potential roles of the identified DEMs related to CLNM in PTC.A total of 316 PTC patients were included to identify DEMs. Two hundred thirty-seven (75%) PTC patients were randomly selected from the 316 patients as a training set, while the remaining 79 (25%) patients were regarded as a testing set for validation. Two DEMs, miRNA-146b-3p (HR: 1.327, 95% CI = 1.135-1.551, P = .000) and miRNA-363-3p (HR: 0.714, 95% CI = 0.528-0.966, P = .029), were significantly associated with CLNM. A risk score based on these 2 DEMs and calculating from multivariate logistic regression analysis, was significantly lower in N0 group over N1a group in both training (N0 vs N1a: 2.04 ±â€Š1.01 vs 2.73 ±â€Š0.61, P = .000) and testing (N0 vs N1a: 2.20 ±â€Š0.93 vs 2.79 ±â€Š0.68, P = .003) sets. The nomogram including risk score, age, and extrathyroidal extension (ETE) was constructed in the training set and was then validated in the testing set, which showed better prediction value than the other three predictors (risk score, age, and ETE) in terms of CLNM identification. Bioinformatics analyses revealed that 5 hub genes, SLC6A1, SYT1, COL19A1, RIMS2, and COL1A2, might involve in pathways including extracellular matrix organization, ion transmembrane transporter activity, axon guidance, and ABC transporters.On the basis of this study, the nomogram including risk score, age, and ETE showed good prediction of CLNM in PTC, which has a potential to facilitate individualized decision for surgical plans.


Assuntos
Metástase Linfática , MicroRNAs/metabolismo , Nomogramas , Câncer Papilífero da Tireoide/metabolismo , Mineração de Dados , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Mapas de Interação de Proteínas , Câncer Papilífero da Tireoide/genética , Câncer Papilífero da Tireoide/patologia
6.
Medicine (Baltimore) ; 99(39): e22413, 2020 Sep 25.
Artigo em Inglês | MEDLINE | ID: mdl-32991472

RESUMO

Stroke is the acute onset of neurological deficits and is associated with high morbidity, mortality, and disease burden. In the present study, we aimed to develop a scientific, nomogram for non-invasive predicting risk for early ischemic stroke, in order to improve stroke prevention efforts among high-risk groups. Data were obtained from a total of 2151 patients with early ischemic stroke from October 2017 to September 2018 and from 1527 healthy controls. Risk factors were examined using logistic regression analyses. Nomogram and receiver operating characteristic (ROC) curves were drawn, cutoff values were established. Significant risk factors for early ischemic stroke included age, sex, blood pressure, history of diabetes, history of genetic, history of coronary heart disease, history of smoking. A nomogram predicting ischemic stroke for all patients had an internally validated concordance index of 0.911. The area under the ROC curve for the logistic regression model was 0.782 (95% confidence interval [CI]: 0.766-0.799, P < .001), with a cutoff value of 2.5. The nomogram developed in this study can be used as a primary non-invasive prevention tool for early ischemic stroke and is expected to provide data support for the revision of current guidelines.


Assuntos
Isquemia Encefálica/epidemiologia , Nomogramas , Acidente Vascular Cerebral/epidemiologia , Adulto , Fatores Etários , Idoso , Consumo de Bebidas Alcoólicas/epidemiologia , Doenças Cardiovasculares/epidemiologia , Diabetes Mellitus/epidemiologia , Feminino , Predisposição Genética para Doença , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Curva ROC , Medição de Risco , Fatores de Risco , Fatores Sexuais , Fumar/epidemiologia
7.
Medicine (Baltimore) ; 99(35): e21721, 2020 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-32871890

RESUMO

The aim of this study was to provide an innovative nomogram to predict the risk of >2 positive nodes in patients fulfilling the Z0011 criteria with 1-2 sentinel lymph nodes (SLNs) only retrieved.From 2007 to 2017, at the Breast Unit of ICS Maugeri Hospital 271 patients with 1-2 macrometastatic SLNs, fulfilling the Z0011 criteria, underwent axillary dissection and were retrospectively reviewed.A mean of 1.5 SLNs per patient were identified and retrieved. One hundred eighty-seven (69.0%) had 1-2 positive nodes, and 84 (31.0%) had >2 metastatic nodes. Independent predictors of axillary status were: positive SLNs/retrieved SLNs ratio (odds ratio [OR] 10.95, P = .001), extranodal extension (OR 5.51, P = .0002), and multifocal disease (OR 2.9, P = .003). A nomogram based on these variables was constructed (area under curve after bootstrap = 0.74).The proposed nomogram might select those patients fulfilling the Z0011 criteria, with 1-2 SLNs harvested, in whom a high axillary tumor burden is expected, aiding to guide adjuvant treatments.


Assuntos
Neoplasias da Mama/patologia , Neoplasias Primárias Múltiplas/patologia , Nomogramas , Linfonodo Sentinela/patologia , Idoso , Antineoplásicos Hormonais/uso terapêutico , Área Sob a Curva , Axila , Neoplasias da Mama/terapia , Quimioterapia Adjuvante , Feminino , Humanos , Metástase Linfática , Mastectomia Segmentar , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Radioterapia Adjuvante , Carga Tumoral
8.
Medicine (Baltimore) ; 99(33): e21798, 2020 Aug 14.
Artigo em Inglês | MEDLINE | ID: mdl-32872080

RESUMO

This study is to establish the nomogram model and provide clinical therapy decision-making for extensive-stage small-cell lung cancer (ES-SCLC) patients with different metastatic sites using the Surveillance, Epidemiology, and End Results (SEER) Program.A total of 10,025 patients of ES-SCLC with metastasis from January 2010 to December 2016 were enrolled from the SEER database. All samples were randomly divided into a derivation cohort and a validation cohort, and the derivation cohort was divided into 6 groups by different metastatic sites: bone, liver, lung, brain, multiple organs, and other organs. Using Cox proportional hazards models to analyze candidate prognostic factors, screening out the independent prognostic factors to establish the nomogram. Compare the different models by Net reclassification improvement and integrated discrimination improvement. Concordance index (C-index) and the calibration curve were used to verify the prediction efficiency of the nomogram in the derivation cohort and validation cohort.In the derivation cohort, the median overall survival was 7 months. The overall survival rates at 6-month, 1-year, and 2-year were 55.07%, 24.61%, and 7.56%, respectively. The median survival time was 10, 8, 7, 9, 7, and 6 months for the 6 groups of different metastatic sites: other, bone, liver, lung, brain, and multiple organs, respectively. Age, sex, race, T, N, distant metastatic site, and chemotherapy were contained in the final nomogram prognostic model. The C-index was 0.6569777 in the derivation cohort and 0.8386301 in the validation cohort.The survival time of ES-SCLC patients with different metastatic sites was significantly different. The nomogram can effectively predict the prognosis of individuals and provide a basis for clinical decision-making.


Assuntos
Neoplasias Pulmonares/mortalidade , Nomogramas , Carcinoma de Pequenas Células do Pulmão/mortalidade , Adulto , Idoso , Feminino , Humanos , Neoplasias Pulmonares/diagnóstico , Masculino , Pessoa de Meia-Idade , Programa de SEER , Carcinoma de Pequenas Células do Pulmão/diagnóstico , Estados Unidos/epidemiologia
9.
J Transl Med ; 18(1): 328, 2020 08 31.
Artigo em Inglês | MEDLINE | ID: mdl-32867787

RESUMO

BACKGROUND: Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. METHODS: 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. RESULTS: Age, neutrophil-to-lymphocyte ratio, D-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC > 101) was more than 50%, respectively. CONCLUSION: The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management.


Assuntos
Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/mortalidade , Escore de Alerta Precoce , Nomogramas , Pneumonia Viral/diagnóstico , Pneumonia Viral/mortalidade , Adulto , Idoso , Betacoronavirus/fisiologia , China/epidemiologia , Estudos de Coortes , Feminino , História do Século XXI , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Prognóstico , Estudos Retrospectivos , Medição de Risco , Fatores de Risco
10.
Medicine (Baltimore) ; 99(35): e21304, 2020 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-32871861

RESUMO

To determine the efficacy of neoadjuvant chemoradiotherapy (NCRT) between young and old patients with locally advanced rectal cancer (LARC) in terms of tumor response and survival outcome.LARC patients undergoing NCRT and radical surgery from 2011 to 2015 were included and divided into: young (aged ≤50 years) and old group (aged >50 years). Multivariate analyses were performed to identify risk factors for local recurrence. Least absolute shrinkage and selection operator analysis was performed to identify risk factors for overall survival. Predicting nomograms and time-indepent receiver operating characteristic curve analysis were performed to compare the models containing with/withour age groups.A total of 572 LARC patients were analyzed. The young group was associated with higher pathological TNM stage, poorly differentiated tumors, and higher rate of positive distal resection margin (P = .010; P = .019; P = .023 respectively). Young patients were associated with poorer 5-year disease-free survival and local recurrence rates (P = .023, P = .003 respectively). Cox regression analysis demonstrated that age ≤50 years (Hazard ratio = 2.994, P = .038) and higher pathological TNM stage (Hazard ratio = 3.261, P = .005) were significantly associated with increased risk for local recurrence. Least absolute shrinkage and selection operator analysis and the time-indepent receiver operating characteristic curve analysis demonstrated that including the age group were superior than that without age group.Young patients were associated with poorer disease free survival (DFS) and a higher risk for local recurrence in LARC following NCRT. The predicting model basing based on the age group had a better predictive ability. More intense adjuvant treatment could be considered to improve DFS and local control for young patients with LARC following NCRT.


Assuntos
Terapia Neoadjuvante/métodos , Recidiva Local de Neoplasia/mortalidade , Neoplasias Retais/patologia , Neoplasias Retais/terapia , Adulto , Idoso , Quimiorradioterapia/métodos , Intervalo Livre de Doença , Feminino , Humanos , Masculino , Margens de Excisão , Pessoa de Meia-Idade , Estadiamento de Neoplasias/métodos , Nomogramas , Valor Preditivo dos Testes , Prognóstico , Estudos Retrospectivos , Fatores de Risco , Resultado do Tratamento
11.
J Immunother Cancer ; 8(2)2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32895296

RESUMO

BACKGROUND: Individualized prediction of mortality risk can inform the treatment strategy for patients with COVID-19 and solid tumors and potentially improve patient outcomes. We aimed to develop a nomogram for predicting in-hospital mortality of patients with COVID-19 with solid tumors. METHODS: We enrolled patients with COVID-19 with solid tumors admitted to 32 hospitals in China between December 17, 2020, and March 18, 2020. A multivariate logistic regression model was constructed via stepwise regression analysis, and a nomogram was subsequently developed based on the fitted multivariate logistic regression model. Discrimination and calibration of the nomogram were evaluated by estimating the area under the receiver operator characteristic curve (AUC) for the model and by bootstrap resampling, a Hosmer-Lemeshow test, and visual inspection of the calibration curve. RESULTS: There were 216 patients with COVID-19 with solid tumors included in the present study, of whom 37 (17%) died and the other 179 all recovered from COVID-19 and were discharged. The median age of the enrolled patients was 63.0 years and 113 (52.3%) were men. Multivariate logistic regression revealed that increasing age (OR=1.08, 95% CI 1.00 to 1.16), receipt of antitumor treatment within 3 months before COVID-19 (OR=28.65, 95% CI 3.54 to 231.97), peripheral white blood cell (WBC) count ≥6.93 ×109/L (OR=14.52, 95% CI 2.45 to 86.14), derived neutrophil-to-lymphocyte ratio (dNLR; neutrophil count/(WBC count minus neutrophil count)) ≥4.19 (OR=18.99, 95% CI 3.58 to 100.65), and dyspnea on admission (OR=20.38, 95% CI 3.55 to 117.02) were associated with elevated mortality risk. The performance of the established nomogram was satisfactory, with an AUC of 0.953 (95% CI 0.908 to 0.997) for the model, non-significant findings on the Hosmer-Lemeshow test, and rough agreement between predicted and observed probabilities as suggested in calibration curves. The sensitivity and specificity of the model were 86.4% and 92.5%. CONCLUSION: Increasing age, receipt of antitumor treatment within 3 months before COVID-19 diagnosis, elevated WBC count and dNLR, and having dyspnea on admission were independent risk factors for mortality among patients with COVID-19 and solid tumors. The nomogram based on these factors accurately predicted mortality risk for individual patients.


Assuntos
Infecções por Coronavirus/mortalidade , Mortalidade Hospitalar , Neoplasias/terapia , Nomogramas , Pneumonia Viral/mortalidade , Fatores Etários , Idoso , Área Sob a Curva , Betacoronavirus , China/epidemiologia , Estudos de Coortes , Infecções por Coronavirus/sangue , Infecções por Coronavirus/complicações , Infecções por Coronavirus/fisiopatologia , Dispneia/fisiopatologia , Fadiga/fisiopatologia , Feminino , Frequência Cardíaca , Humanos , Contagem de Leucócitos , Modelos Logísticos , Neoplasias Pulmonares/complicações , Neoplasias Pulmonares/terapia , Contagem de Linfócitos , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Estadiamento de Neoplasias , Neoplasias/complicações , Neoplasias/patologia , Neutrófilos , Pandemias , Pneumonia Viral/sangue , Pneumonia Viral/complicações , Pneumonia Viral/fisiopatologia , Doença Pulmonar Obstrutiva Crônica/complicações , Curva ROC , Estudos Retrospectivos , Medição de Risco
12.
Medicine (Baltimore) ; 99(36): e21802, 2020 Sep 04.
Artigo em Inglês | MEDLINE | ID: mdl-32899008

RESUMO

Bone is a frequent site for the occurrence of metastasis of thyroid cancer (TC). TC with bone metastasis (TCBM) is associated with skeletal-related events (SREs), with poor prognosis and low overall survival (OS). Therefore, it is necessary to develop a predictive nomogram for prognostic evaluation. This study aimed to construct an effective nomogram for predicting the OS and cancer-specific survival (CSS) of TC patients with BM. Those TC patients with newly diagnosed BM were retrospectively examined over a period of 6 years from 2010 to 2016 using data from the Surveillance, Epidemiology and End Results (SEER) database. Demographics and clinicopathological data were collected for further analysis. Patients were randomly allocated into training and validation cohorts with a ratio of ∼7:3. OS and CSS were retrieved as research endpoints. Univariate and multivariate Cox regression analyses were performed for identifying independent predictors. Overall, 242 patients were enrolled in this study. Age, histologic grade, histological subtype, tumor size, radiotherapy, liver metastatic status, and lung metastatic status were determined as the independent prognostic factors for predicting the OS and CSS in TCBM patients. Based on the results, visual nomograms were separately developed and validated for predicting 1-, 2-, and 3-year OS and CSS in TCBM patients on the ground of above results. The calibration, receiver operating characteristic (ROC) curve and decision curve analysis (DCA) also demonstrated the reliability and accuracy of the clinical prediction model. Our predictive model is expected to be a personalized and easily applicable tool for evaluating the prognosis of TCBM patients, and may contribute toward making an accurate judgment in clinical practice.


Assuntos
Neoplasias Ósseas/secundário , Nomogramas , Neoplasias da Glândula Tireoide/mortalidade , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Modelos de Riscos Proporcionais , Reprodutibilidade dos Testes , Estudos Retrospectivos , Programa de SEER/estatística & dados numéricos , Neoplasias da Glândula Tireoide/patologia , Adulto Jovem
13.
Medicine (Baltimore) ; 99(30): e20703, 2020 Jul 24.
Artigo em Inglês | MEDLINE | ID: mdl-32791664

RESUMO

Few models regarding to the individualized prognosis assessment of oropharyngeal squamous cell carcinoma (OPSCC) patients were documented. The purpose of this study was to establish nomogram model to predict the long-term overall survival (OS) and cancer-specific survival (CSS) of OPSCC patients. The detailed clinical data for the 10,980 OPSCC patients were collected from the surveillance, epidemiology and end results (SEER) database. Furthermore, we applied a popular and reasonable random split-sample method to divide the total 10,980 patients into 2 groups, including 9881 (90%) patients in the modeling cohort and 1099 (10%) patients in the external validation cohort. Among the modeling cohort, 3084 (31.2%) patients were deceased at the last follow-up date. Of those patients, 2188 (22.1%) patients died due to OPSCC. In addition, 896 (9.1%) patients died due to other causes. The median follow-up period was 45 months (1-119 months). We developed 2 nomograms to predict 5- and 8- year OS and CSS using Cox Proportional Hazards model. The nomograms' accuracy was evaluated through the concordance index (C-index) and calibration curves by internal and external validation. The C-indexes of internal validation on the 5- and 8-year OS and CSS were 0.742 and 0.765, respectively. Moreover, the C-indexes of external validation were 0.740 and 0.759, accordingly. Based on a retrospective cohort from the SEER database, we succeeded in constructing 2 nomograms to predict long-term OS and CSS for OPSCC patients, which provides reference for surgeons to develop a treatment plan and individual prognostic evaluations.


Assuntos
Carcinoma de Células Escamosas/mortalidade , Nomogramas , Neoplasias Orofaríngeas/mortalidade , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Programa de SEER , Análise de Sobrevida , Estados Unidos/epidemiologia , Adulto Jovem
14.
Medicine (Baltimore) ; 99(31): e20963, 2020 Jul 31.
Artigo em Inglês | MEDLINE | ID: mdl-32756083

RESUMO

BACKGROUND: The aim of study was to develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) of patients with pseudomyxoma peritonei (PMP) and compare the predictive accuracy with the American Joint Committee on Cancer (AJCC) staging system. METHODS: Data of 4959 PMP patients who underwent surgical resection were collected between 2004 and 2015 from the Surveillance Epidemiology and End Results (SEER) database. All included patients were divided into training (n = 3307) and validation (n = 1652) cohorts. The Kaplan-Meier method and Cox proportional hazard model were applied. Nomograms were validated by discrimination and calibration. Finally, concordance index (C-index) was used to compare the predictive performance of nomograms with that of the AJCC staging system. RESULTS: According to the univariate and multivariate analyses of training sets, both nomograms for predicting OS and CSS combining age, grade, location, N stage, M stage, and chemotherapy were identified. Nomograms predicting OS also incorporated T stage and the number of lymph nodes removed (LNR). The calibration curves showed good consistency between predicted and actual observed survival. Moreover, C-index values demonstrated that the nomograms predicting both OS and CSS were superior to the AJCC staging system in both cohorts. CONCLUSION: We successfully developed and validated prognostic nomograms for predicting OS and CSS in PMP patients. Two nomograms were more accurate and applicable than the AJCC staging system for predicting patient survival, which may help clinicians stratify patients into different risk groups, tailor individualized treatment, and accurately predict patient survival in PMP.


Assuntos
Nomogramas , Neoplasias Peritoneais/diagnóstico , Pseudomixoma Peritoneal/diagnóstico , Adulto , Idoso , Feminino , Humanos , Estimativa de Kaplan-Meier , Masculino , Pessoa de Meia-Idade , Estadiamento de Neoplasias/métodos , Estadiamento de Neoplasias/mortalidade , Neoplasias Peritoneais/mortalidade , Neoplasias Peritoneais/cirurgia , Prognóstico , Intervalo Livre de Progressão , Modelos de Riscos Proporcionais , Pseudomixoma Peritoneal/mortalidade , Pseudomixoma Peritoneal/cirurgia , Reprodutibilidade dos Testes , Programa de SEER , Análise de Sobrevida , Adulto Jovem
15.
Medicine (Baltimore) ; 99(31): e21021, 2020 Jul 31.
Artigo em Inglês | MEDLINE | ID: mdl-32756087

RESUMO

The purpose of this study was to investigate the potential prognostic value of preoperative lymphocyte-to-monocyte ratio (LMR) and establishment of a prognostic nomogram in post surgical patients with gallbladder carcinoma (GBC).Receiver operating characteristic curve analysis was performed to determine the optimal cut-off value of LMR. The correlation between preoperative LMR and overall survival (OS) was analyzed using univariate and multivariate Cox regression analyses. A relevant prognostic nomogram was established.Three hundred fifteen GBC patients were retrospectively enrolled. Based on receiver operating characteristic curve analysis, the optimal cutoff value of LMR was 2.685. Patients were categorized into high-LMR group (n = 143) or low-LMR group (n = 172). Low-LMR value was significantly associated with elderly age, advanced tumor, and the performance of a palliative cholecystectomy. The results of the univariate and multivariate analyses eliminated the degree of tumor differentiation, tumor-node-metastasis stages, surgery types, and LMR as independent predictors of OS. Based on those independent predictors, a predictive nomogram for OS was generated with an accuracy of 0.848.Based on our findings, the predictive nomogram should be included in the routine assessment of GBC patients.


Assuntos
Neoplasias da Vesícula Biliar/diagnóstico , Contagem de Leucócitos , Contagem de Linfócitos , Monócitos , Nomogramas , Adulto , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Neoplasias da Vesícula Biliar/mortalidade , Neoplasias da Vesícula Biliar/patologia , Neoplasias da Vesícula Biliar/cirurgia , Humanos , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Prognóstico , Curva ROC , Reprodutibilidade dos Testes , Estudos Retrospectivos , Análise de Sobrevida
16.
Medicine (Baltimore) ; 99(31): e21322, 2020 Jul 31.
Artigo em Inglês | MEDLINE | ID: mdl-32756116

RESUMO

A competing-risks model was developed in this study to identify the significant prognostic factors and evaluate the cumulative incidence of cause-specific death in gallbladder adenocarcinoma (GBAC), with the aim of providing guidance on effective clinical treatments.All patients with GBAC in the Surveillance, Epidemiology, and End Results (SEER) database during 1973 to 2015 were identified. The potential prognostic factors were identified using competing-risks analyses implemented using the R and SAS statistical software packages. We calculated the cumulative incidence function (CIF) for cause-specific death and death from other causes at each time point. The Fine-Gray proportional-subdistribution-hazards model was then applied in univariate and multivariate analyses to test the differences in CIF between different groups and identify independent prognostic factors.This study included 3836 eligible patients who had been enrolled from 2004 to 2015 in the SEER database. The univariate analysis indicated that age, race, AJCC stage, RS, tumor size, SEER historic stage, grade, surgery, radiotherapy, chemotherapy and adjuvant therapy (RCT, SRT, SCT and SRCT) were significant factors affecting the probability of death due to GBAC. The multivariate analysis indicated that age, race, AJCC stage, RS status, tumor size, grade and SRT were independent prognostic factors affecting GBAC cancer-specific death. A nomogram model was constructed based on multivariate models for death related to GBAC.We have constructed the first competing-risks nomogram for GBAC. The model was found to perform well. This novel validated prognostic model may facilitate the choosing of beneficial treatment strategies and help when predicting survival.


Assuntos
Adenocarcinoma/mortalidade , Neoplasias da Vesícula Biliar/mortalidade , Nomogramas , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Medição de Risco , Programa de SEER/estatística & dados numéricos , Adulto Jovem
17.
Medicine (Baltimore) ; 99(31): e21339, 2020 Jul 31.
Artigo em Inglês | MEDLINE | ID: mdl-32756121

RESUMO

Patients with non-small-cell lung cancer (NSCLC) often have a poor prognosis when brain metastases (BM) occur. This study aimed to evaluate the prognostic factors of BM in newly diagnosed NSCLC patients and construct a nomogram to predict the overall survival (OS).We included NSCLC patients with BM newly diagnosed from 2010 to 2015 in Surveillance, Epidemiology, and End Results database. The independent prognostic factors for NSCLC with BM were determined by Cox proportional hazards regression analysis. We then constructed and validated a nomogram to predict the OS of NSCLC with BM.We finally included 4129 NSCLC patients with BM for analysis. Age, race, sex, liver metastasis, primary site, histologic type, grade, bone metastasis, T stage, N stage, surgery, chemotherapy, and lung metastasis were identified as the prognostic factors for NSCLC with BM and integrated to establish the nomogram. The calibration, receiver operating characteristic curve, and decision curve analyses also showed that the clinical prediction model performed satisfactorily in predicting prognosis.A clinical prediction model was constructed and validated to predict individual OS for NSCLC with BM. The establishment of this clinical prediction model has great significance for clinicians and individuals.


Assuntos
Neoplasias Encefálicas/secundário , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Neoplasias Pulmonares/mortalidade , Nomogramas , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Modelos de Riscos Proporcionais , Curva ROC , Adulto Jovem
18.
Medicine (Baltimore) ; 99(34): e21693, 2020 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-32846785

RESUMO

The role of immune cell infiltration in the prognosis of clear cell renal cell carcinoma (ccRCC) has received increasing attention. However, immune scores have not yet been introduced into routine clinical practice of ccRCC patients. The principal objective of our research was to study the correlation between immune scores and overall survival (OS) of ccRCC.In this study, Cox regression analyses were used to identify risk factors associated with OS of ccRCC based on the Cancer Genome Atlas datasets. Furthermore, an integrated nomogram combining immune scores and clinicopathologic factors was built for predicting 3- and 5-year OS of ccRCC patients. The receiver operating characteristic curve, concordance index, and calibration curves were used for the evaluation of our nomogram. Also, Kaplan-Meier (KM) survival analysis of immune scores, stromal scores, and different clinicopathological factors was performed.A total of 514 patients were divided into the low- or high-immune scores group. KM and multivariate Cox regression analyses demonstrated that ccRCC patients with high-immune scores had significantly poor OS compared with those with low-immune scores. Calibration curves showed good consistency between the predicted OS and the actual OS probability. Areas under the receiver operating characteristic curves for 3- and 5-year OS were 0.816 and 0.769, and the concordance index was 0.775, indicating that our nomogram had good accuracy for predicting OS of ccRCC patients. Additionally, KM analysis showed that older age, later T stage, distant metastasis, advanced tumor lymph node metastasis stage, higher tumor grade, left site, and low stromal scores were associated with worse OS in ccRCC patients.High-immune scores show a significant correlation with unsatisfactory prognosis in ccRCC patients. Furthermore, the immune scores-based nomogram may be helpful in predicting ccRCC prognosis.


Assuntos
Carcinoma de Células Renais/imunologia , Carcinoma de Células Renais/mortalidade , Neoplasias Renais/imunologia , Neoplasias Renais/mortalidade , Nomogramas , Idoso , Idoso de 80 Anos ou mais , Correlação de Dados , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Prognóstico , Taxa de Sobrevida
19.
Nat Commun ; 11(1): 4308, 2020 08 27.
Artigo em Inglês | MEDLINE | ID: mdl-32855399

RESUMO

Distant metastasis (DM) is the main cause of treatment failure in locally advanced rectal cancer. Adjuvant chemotherapy is usually used for distant control. However, not all patients can benefit from adjuvant chemotherapy, and particularly, some patients may even get worse outcomes after the treatment. We develop and validate an MRI-based radiomic signature (RS) for prediction of DM within a multicenter dataset. The RS is proved to be an independent prognostic factor as it not only demonstrates good accuracy for discriminating patients into high and low risk of DM in all the four cohorts, but also outperforms clinical models. Within the stratified analysis, good chemotherapy efficacy is observed for patients with pN2 disease and low RS, whereas poor chemotherapy efficacy is detected in patients with pT1-2 or pN0 disease and high RS. The RS may help individualized treatment planning to select patients who may benefit from adjuvant chemotherapy for distant control.


Assuntos
Antineoplásicos/uso terapêutico , Nomogramas , Protectomia , Neoplasias Retais/terapia , Reto/diagnóstico por imagem , Adulto , Idoso , Quimioterapia Adjuvante/estatística & dados numéricos , Conjuntos de Dados como Assunto , Intervalo Livre de Doença , Feminino , Seguimentos , Humanos , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Terapia Neoadjuvante/estatística & dados numéricos , Metástase Neoplásica/diagnóstico , Metástase Neoplásica/prevenção & controle , Estadiamento de Neoplasias , Planejamento de Assistência ao Paciente , Seleção de Pacientes , Radioterapia Adjuvante/estatística & dados numéricos , Neoplasias Retais/diagnóstico por imagem , Neoplasias Retais/patologia , Reto/patologia , Reto/cirurgia , Reprodutibilidade dos Testes , Estudos Retrospectivos , Medição de Risco/métodos
20.
Medicine (Baltimore) ; 99(30): e21163, 2020 Jul 24.
Artigo em Inglês | MEDLINE | ID: mdl-32791689

RESUMO

Autophagy, a major cause of cancer-related death, is correlated with the pathogenesis of various diseases including cancers. Our study aimed to develop an autophagy-related model for predicting prognosis of patients with laryngeal cancer.We analyzed the correlation between expression profiles of autophagy-related genes (ARGs) and clinical outcomes in 111 laryngeal cancer patients from The Cancer Genome Atlas (TCGA). Afterward, gene functional enrichment analyses of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to find the major biological attributes. Univariate Cox regression analyses and multivariate Cox regression analyses were performed to screen ARGs whose expression profiles were significantly associated with laryngeal cancer patients overall survival (OS). Furthermore, to provide the doctors and patients with a quantitative method to perform an individualized survival prediction, we constructed a prognostic nomogram.Thirty eight differentially expressed ARGs were screened out in laryngeal cancer patients through the TCGA database. Related functional enrichments may act as tumor-suppressive roles in the tumorigenesis of laryngeal cancer. Subsequently, 4 key prognostic ARGs (IKBKB, ST13, TSC2, and MAP2K7) were identified from all ARGs by the Cox regression model, which significantly correlated with OS in laryngeal cancer. Furthermore, the risk score was constructed, which significantly divided laryngeal cancer patients into high- and low-risk groups. Integrated with clinical characteristics, gender, N and the risk score are very likely associated with patients OS. A prognostic nomogram of ARGs was constructed using the Cox regression model.Our study could provide a valuable prognostic model for predicting the prognosis of laryngeal cancer patients and a new understanding of autophagy in laryngeal cancer.


Assuntos
Autofagia/genética , Neoplasias Laríngeas/genética , Nomogramas , Fatores Etários , Proteínas de Transporte/genética , Perfilação da Expressão Gênica , Humanos , Quinase I-kappa B/genética , Neoplasias Laríngeas/patologia , MAP Quinase Quinase 7/genética , Modelos Biológicos , Estadiamento de Neoplasias , Prognóstico , Modelos de Riscos Proporcionais , Fatores de Risco , Fatores Sexuais , Taxa de Sobrevida , Transcriptoma , Proteína 2 do Complexo Esclerose Tuberosa/genética , Proteínas Supressoras de Tumor/genética
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