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1.
BMC Musculoskelet Disord ; 25(1): 141, 2024 Feb 14.
Artigo em Inglês | MEDLINE | ID: mdl-38355520

RESUMO

BACKGROUND: Anemia is a common complication of total hip arthroplasty (THA). In this study, we evaluated the preoperative risk factors for postoperative anemia after THA and developed a nomogram model based on related preoperative and intraoperative factors. METHODS: From January 2020 to May 2023, 927 THA patients at the same medical center were randomly assigned to either the training or validation cohort. The correlation between preoperative and intraoperative risk factors and postoperative anemia after THA was evaluated using univariate and multivariate logistic regression analysis. A nomogram was developed using these predictive variables. The effectiveness and validation for the clinical application of this nomogram were evaluated using the concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). RESULTS: Through univariate and multivariate logistic regression analysis, 7 independent predictive factors were identified in the training cohort: Lower body mass index (BMI), extended operation time, greater intraoperative bleeding, lower preoperative hemoglobin level, abnormally high preoperative serum amyloid A (SAA) level, history of cerebrovascular disease, and history of osteoporosis. The C-index of the model was 0.871, while the AUC indices for the training and validation cohorts were 84.4% and 87.1%, respectively. In addition, the calibration curves of both cohorts showed excellent consistency between the observed and predicted probabilities. The DCA curves of the training and validation cohorts were high, indicating the high clinical applicability of the model. CONCLUSIONS: Lower BMI, extended operation time, increased intraoperative bleeding, reduced preoperative hemoglobin level, elevated preoperative SAA level, history of cerebrovascular disease, and history of osteoporosis were seven independent preoperative risk factors associated with postoperative anemia after THA. The nomogram developed could aid in predicting postoperative anemia, facilitating advanced preparation, and enhancing blood management. Furthermore, the nomogram could assist clinicians in identifying patients most at risk for postoperative anemia.


Assuntos
Anemia , Artroplastia de Quadril , Transtornos Cerebrovasculares , Osteoporose , Humanos , Artroplastia de Quadril/efeitos adversos , Nomogramas , Anemia/diagnóstico , Anemia/epidemiologia , Anemia/etiologia , Redução de Peso , Hemoglobinas , Estudos Retrospectivos
2.
BMC Surg ; 24(1): 56, 2024 Feb 14.
Artigo em Inglês | MEDLINE | ID: mdl-38355554

RESUMO

OBJECTIVES: In this study, we aimed to develop a multiparameter prediction model to improve the diagnostic accuracy of invasive adenocarcinoma in pulmonary pure glass nodules. METHOD: We included patients with pulmonary pure glass nodules who underwent lung resection and had a clear pathology between January 2020 and January 2022 at the Qilu Hospital of Shandong University. We collected data on the clinical characteristics of the patients as well as their preoperative biomarker results and computed tomography features. Thereafter, we performed univariate and multivariate logistic regression analyses to identify independent risk factors, which were then used to develop a prediction model and nomogram. We then evaluated the recognition ability of the model via receiver operating characteristic (ROC) curve analysis and assessed its calibration ability using the Hosmer-Lemeshow test and calibration curves. Further, to assess the clinical utility of the nomogram, we performed decision curve analysis. RESULT: We included 563 patients, comprising 174 and 389 cases of invasive and non-invasive adenocarcinoma, respectively, and identified seven independent risk factors, namely, maximum tumor diameter, age, serum amyloid level, pleural effusion sign, bronchial sign, tumor location, and lobulation. The area under the ROC curve was 0.839 (95% CI: 0.798-0.879) for the training cohort and 0.782 (95% CI: 0.706-0.858) for the validation cohort, indicating a relatively high predictive accuracy for the nomogram. Calibration curves for the prediction model also showed good calibration for both cohorts, and decision curve analysis showed that the clinical prediction model has clinical utility. CONCLUSION: The novel nomogram thus constructed for identifying invasive adenocarcinoma in patients with isolated pulmonary pure glass nodules exhibited excellent discriminatory power, calibration capacity, and clinical utility.


Assuntos
Adenocarcinoma , Neoplasias Pulmonares , Humanos , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/cirurgia , Modelos Estatísticos , Prognóstico , Estudos Retrospectivos , Adenocarcinoma/diagnóstico por imagem , Adenocarcinoma/cirurgia , Nomogramas
3.
Sci Rep ; 14(1): 3500, 2024 02 12.
Artigo em Inglês | MEDLINE | ID: mdl-38347041

RESUMO

Long non-coding RNAs (lncRNAs) involved in metabolism are recognized as significant factors in breast cancer (BC) progression. We constructed a novel prognostic signature for BC using metabolism-related lncRNAs and investigated their underlying mechanisms. The training and validation cohorts were established from BC patients acquired from two public sources: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The prognostic signature of metabolism-related lncRNAs was constructed using the least absolute shrinkage and selection operator (LASSO) cox regression analysis. We developed and validated a new prognostic risk model for BC using the signature of metabolism-related lncRNAs (SIRLNT, SIAH2-AS1, MIR205HG, USP30-AS1, MIR200CHG, TFAP2A-AS1, AP005131.2, AL031316.1, C6orf99). The risk score obtained from this signature was proven to be an independent prognostic factor for BC patients, resulting in a poor overall survival (OS) for individuals in the high-risk group. The area under the curve (AUC) for OS at three and five years were 0.67 and 0.65 in the TCGA cohort, and 0.697 and 0.68 in the GEO validation cohort, respectively. The prognostic signature demonstrated a robust association with the immunological state of BC patients. Conventional chemotherapeutics, such as docetaxel and paclitaxel, showed greater efficacy in BC patients classified as high-risk. A nomogram with a c-index of 0.764 was developed to forecast the survival time of BC patients, considering their risk score and age. The silencing of C6orf99 markedly decreased the proliferation, migration, and invasion capacities in MCF-7 cells. Our study identified a signature of metabolism-related lncRNAs that predicts outcomes in BC patients and could assist in tailoring personalized prevention and treatment plans.


Assuntos
Neoplasias da Mama , RNA Longo não Codificante , Humanos , Feminino , Neoplasias da Mama/genética , RNA Longo não Codificante/genética , Prognóstico , Nomogramas , Docetaxel
4.
Sci Rep ; 14(1): 3543, 2024 02 12.
Artigo em Inglês | MEDLINE | ID: mdl-38347044

RESUMO

Closed femoral shaft fracture is caused by high-energy injuries, and non-union exists after operation, which can significantly damage patients' body and mind. This study aimed to explore the factors influencing postoperative non-union of closed femoral shaft fractures and establish a predictive nomogram. Patients with closed femoral shaft fractures treated at Hebei Medical University Third Hospital between January 2015 and December 2021 were retrospectively enrolled. A total of 729 patients met the inclusion criteria; of them, those treated in 2015-2019 comprised the training cohort (n = 617), while those treated in 2020-2021 comprised the external validation cohort (n = 112). According to multivariate logistic regression analysis, complex fractures, bone defects, smoking, and postoperative infection were independent risk factors. Based on the factors, a predictive nomogram was constructed and validated. The C-indices in training and external validation cohorts were 0.818 and 0.781, respectively; and the C-index of internal validation via bootstrap resampling was 0.804. The Hosmer-Lemeshow test showed good fit of the nomogram (P > 0.05) consistent with the calibration plot results. The clinical effectiveness was best at a threshold probability of 0.10-0.40 in decision curve analysis. The risk prediction for patients with fractures using this nomogram may aid targeted prevention and rehabilitation programs.


Assuntos
Fraturas do Fêmur , Nomogramas , Humanos , Estudos Retrospectivos , Fraturas do Fêmur/cirurgia , Hospitais Universitários , Fatores de Risco
5.
Sci Rep ; 14(1): 3561, 2024 02 12.
Artigo em Inglês | MEDLINE | ID: mdl-38347099

RESUMO

The implementation of primary tumor resection (PTR) in the treatment of kidney cancer patients (KC) with bone metastases (BM) has been controversial. This study aims to construct the first tool that can accurately predict the likelihood of PTR benefit in KC patients with BM (KCBM) and select the optimal surgical candidates. This study acquired data on all patients diagnosed with KCBM during 2010-2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (PSM) was utilized to achieve balanced matching of PTR and non-PTR groups to eliminate selection bias and confounding factors. The median overall survival (OS) of the non-PTR group was used as the threshold to categorize the PTR group into PTR-beneficial and PTR-Nonbeneficial subgroups. Kaplan-Meier (K-M) survival analysis was used for comparison of survival differences and median OS between groups. Risk factors associated with PTR-beneficial were identified using univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC), area under the curve (AUC), calibration curves, and decision curve analysis (DCA) were used to validate the predictive performance and clinical utility of the nomogram. Ultimately, 1963 KCBM patients meeting screening criteria were recruited. Of these, 962 patients received PTR and the remaining 1061 patients did not receive PTR. After 1:1 PSM, there were 308 patients in both PTR and non-PTR groups. The K-M survival analysis results showed noteworthy survival disparities between PTR and non-PTR groups, both before and after PSM (p < 0.001). In the logistic regression results of the PTR group, histological type, T/N stage and lung metastasis were shown to be independent risk factors associated with PTR-beneficial. The web-based nomogram allows clinicians to enter risk variables directly and quickly obtain PTR beneficial probabilities. The validation results showed the excellent predictive performance and clinical utility of the nomograms for accurate screening of optimal surgical candidates for KCBM. This study constructed an easy-to-use nomogram based on conventional clinicopathologic variables to accurately select the optimal surgical candidates for KCBM patients.


Assuntos
Neoplasias Ósseas , Neoplasias Renais , Humanos , Detecção Precoce de Câncer , Neoplasias Ósseas/cirurgia , Área Sob a Curva , Neoplasias Renais/cirurgia , Nomogramas , Pontuação de Propensão , Programa de SEER , Prognóstico
6.
BMC Cancer ; 24(1): 193, 2024 Feb 12.
Artigo em Inglês | MEDLINE | ID: mdl-38347528

RESUMO

BACKGROUND: Prognosis prediction for pancreatic cancer has always been difficult in clinical practice because of its high heterogeneity and mortality. The aim of the study was to assess the value of prognostic immune-inflammatory-nutritional (PIIN) score on overall survival (OS) in postoperative patients with pancreatic cancer and to develop a nomogram incorporating PIIN score. METHODS: This study retrospectively analyzed the clinic pathological data of 155 patients with pancreatic cancer who underwent radical surgery. PIIN score was calculated by measuring the fibrinogen (FIB), neutrophil to lymphocyte ratio (NLR), systemic immune-inflammation index (SII), albumin-bilirubin (ALBI) score, and prognostic nutritional index (PNI). Patients were divided into two groups by PIIN score levels over a threshold of 37.2. Univariate and multivariate analysis were performed using the Cox regression analysis model. The time-dependent receiver operating characteristic (ROC) curve was plotted to compare the prognostic values of the scoring systems. Finally, a nomogram based on PIIN score was constructed and validated. RESULTS: Multivariate regression analysis showed that PIIN score (hazard ratio (HR) = 2.171, 95% confidence interval (CI) = 1.207-3.906, P = 0.010), lymphovascular invasion (HR = 1.663, 95% CI = 1.081-2.557, P = 0.021), poor tumor grade (HR = 2.577, 95% CI = 1.668-3.982, P < 0.001), bad TNM stage (I vs. II: HR = 1.791, 95% CI = 1.103-2.906, P = 0.018; I vs. III: HR = 4.313, 95% CI = 2.365-7.865, P < 0.001) and without adjuvant chemotherapy (HR = 0.552, 95% CI = 0.368-0.829, P = 0.004) were independent risk factors for OS. The time-dependent ROC curves revealed that PIIN score was better than the other scoring systems in predicting survival prognosis. And last, the nomogram established from independent factors such as PIIN score had good predictive power for OS. The ROC curve results showed that the AUC values for 1, 3 and 5 years were 0.826, 0.798 and 0.846, respectively. The calibration plots showed the superior clinical applicability of the nomogram. CONCLUSION: The nomogram model based on PIIN score can be utilized as one of the prognosis stratifications as well as postoperative follow-up for the development of individual treatment for pancreatic cancer.


Assuntos
Nomogramas , Neoplasias Pancreáticas , Humanos , Estudos Retrospectivos , Prognóstico , Fatores de Risco , Neoplasias Pancreáticas/cirurgia
7.
PLoS One ; 19(2): e0298125, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38346070

RESUMO

The tumor heterogeneity is an important cause of clinical therapy failure and yields distinct prognosis in ovarian cancer (OV). Using the advantages of integrated single cell RNA sequencing (scRNA-seq) and bulk data to decode tumor heterogeneity remains largely unexplored. Four public datasets were enrolled in this study, including E-MTAB-8107, TCGA-OV, GSE63885, and GSE26193 cohorts. Random forest algorithm was employed to construct a multi-gene prognostic panel and further evaluated by receiver operator characteristic (ROC), calibration curve, and Cox regression. Subsequently, molecular characteristics were deciphered, and treatments strategies were explored to deliver precise therapy. The landscape of cell subpopulations and functional characteristics, as well as the dynamic of macrophage cells were detailly depicted at single cell level, and then screened prognostic candidate genes. Based on the expression of candidate genes, a stable and robust cell characterized gene associated prognosis signature (CCIS) was developed, which harbored excellent performance at prognosis assessment and patient stratification. The ROC and calibration curves, and Cox regression analysis elucidated CCIS could serve as serve as an independent factor for predicting prognosis. Moreover, a promising clinical tool nomogram was also constructed according to stage and CCIS. Through comprehensive investigations, patients in low-risk group were charactered by favorable prognosis, elevated genomic variations, higher immune cell infiltrations, and superior antigen presentation. For individualized treatment, patients in low-risk group were inclined to better immunotherapy responses. This study dissected tumor heterogeneity and afforded a promising prognostic signature, which was conducive to facilitating clinical outcomes for patients with OV.


Assuntos
Neoplasias Ovarianas , Humanos , Feminino , Prognóstico , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/terapia , Imunoterapia , Nomogramas , Apresentação de Antígeno
8.
Clin Exp Hypertens ; 46(1): 2304023, 2024 Dec 31.
Artigo em Inglês | MEDLINE | ID: mdl-38346228

RESUMO

OBJECTIVES: The objective was to utilize a smartwatch sphygmomanometer to predict new-onset hypertension within a short-term follow-up among individuals with high-normal blood pressure (HNBP). METHODS: This study consisted of 3180 participants in the training set and 1000 participants in the validation set. Participants underwent both ambulatory blood pressure monitoring (ABPM) and home blood pressure monitoring (HBPM) using a smartwatch sphygmomanometer. Multivariable Cox regressions were used to analyze cumulative events. A nomogram was constructed to predict new-onset hypertension. Discrimination and calibration were assessed using the C-index and calibration curve, respectively. RESULTS: Among the 3180 individuals with HNBP in the training set, 693 (21.8%) developed new-onset hypertension within a 6-month period. The nomogram for predicting new-onset hypertension had a C-index of 0.854 (95% CI, 0.843-0.867). The calibration curve demonstrated good agreement between the nomogram's predicted probabilities and actual observations for short-term new-onset hypertension. In the validate dataset, during the 6-month follow-up, the nomogram had a good C-index of 0.917 (95% CI, 0.904-0.930) and a good calibration curve. As the score increased, the risk of new-onset hypertension significantly increased, with an HR of 8.415 (95% CI: 5.153-13.744, p = .000) for the middle-score vs. low-score groups and 86.824 (95% CI: 55.071-136.885, p = .000) for the high-score vs. low-score group. CONCLUSIONS: This study provides evidence for the use of smartwatch sphygmomanometer to monitor blood pressure in individuals at high risk of developing new-onset hypertension in the near future. TRIAL REGISTRATION: ChiCTR2200057354.


Assuntos
Monitorização Ambulatorial da Pressão Arterial , Hipertensão , Humanos , Pressão Sanguínea/fisiologia , Estudos de Coortes , Hipertensão/diagnóstico , Hipertensão/etiologia , Esfigmomanômetros , Nomogramas
9.
Medicine (Baltimore) ; 103(6): e37233, 2024 Feb 09.
Artigo em Inglês | MEDLINE | ID: mdl-38335389

RESUMO

Intratumoral hypoxia is widely associated with the development of malignancy, treatment resistance, and worse prognoses. This study aims to investigate the role of hypoxia-related genes (HRG) in the immune landscape, treatment response, and prognosis of head and neck squamous cell carcinoma (HNSCC). The transcriptome and clinical data of HNSCC were downloaded from TCGA and GEO databases, and HNSCC molecular subtypes were identified using non-negative matrix factorization (NMF) clustering. Prognostic models were constructed using univariate, Lasso, and multivariate Cox regression analyses. The relationship between HRGs and immune cell infiltration, immune therapy response, and drug sensitivity was evaluated, and a nomogram was constructed. 47 HRGs were differentially expressed in HNSCC, among which 10 genes were significantly associated with HNSCC prognosis. Based on these 10 genes, 2 HNSCC molecular subtypes were identified, which showed significant heterogeneity in terms of prognosis, immune infiltration, and treatment response. A total of 3280 differentially expressed genes were identified between the subtypes. After univariate, Lasso, and multivariate Cox regression analysis, 18 genes were selected to construct a novel prognostic model, which showed a significant correlation with B cells, T cells, and macrophages. Using this model, HNSCC was classified into high-risk and low-risk groups, which exhibited significant differences in terms of prognosis, immune cell infiltration, immune therapy response, and drug sensitivity. Finally, a nomogram based on this model and radiotherapy was constructed, which showed good performance in predicting HNSCC prognosis and guiding personalized treatment strategies. The decision curve analysis demonstrated its better clinical applicability compared to other strategies. HRGs can identify 2 HNSCC molecular subtypes with significant heterogeneity, and the HRG-derived risk model has the potential for prognostic prediction and guiding personalized treatment strategies.


Assuntos
Neoplasias de Cabeça e Pescoço , Nomogramas , Humanos , Carcinoma de Células Escamosas de Cabeça e Pescoço/genética , Carcinoma de Células Escamosas de Cabeça e Pescoço/terapia , Prognóstico , Hipóxia , Neoplasias de Cabeça e Pescoço/genética , Neoplasias de Cabeça e Pescoço/terapia
10.
Medicine (Baltimore) ; 103(6): e37048, 2024 Feb 09.
Artigo em Inglês | MEDLINE | ID: mdl-38335439

RESUMO

Antineutrophil cytoplasmic antibody vasculitis-associated interstitial lung disease (AAV-ILD) is a potentially life-threatening disease. However, very little research has been done on the condition's mortality risk. Hence, our objective is to find out the factors influencing the prognosis of AAV-ILD and employ these findings to create a nomogram model. Patients with AAV-ILD who received treatment at the First Affiliated Hospital of Zhengzhou University during the period from March 1, 2011, to April 1, 2022 were selected for this research. The development of nomogram entailed a synergistic integration of univariate, Lasso, and multivariate Cox regression analyses. Internal validation ensued through bootstrap techniques involving 1000 re-sampling iterations. Discrimination and calibration were assessed utilizing Harrell's C-index, receiver operating characteristic (ROC) curve, and calibration curve. Model performance was evaluated through integrated discrimination improvement (IDI), net reclassification improvement (NRI), and likelihood ratio test. The net benefit of the model was evaluated using decision curve analysis (DCA). A cohort comprising 192 patients was enrolled for analysis. Throughout observation period, 32.29% of the population died. Key factors such as cardiac involvement, albumin, smoking history, and age displayed substantial prognostic relevance in AAV-ILD. These factors were incorporated to craft a predictive nomogram. Impressively, the model exhibited robust performance, boasting a Harrell's C index of 0.826 and an AUC of 0.940 (95% CI 0.904-0.976). The calibration curves depicted a high degree of harmony between predicted outcomes and actual observations. Significantly enhancing discriminative ability compared to the ILD-GAP model, the nomogram was validated through the IDI, NRI, and likelihood ratio test. DCA underscored the superior predictive value of the predictive model over the ILD-GAP model. The internal validation further affirmed this efficacy, with a mean Harrell's C-index of 0.815 for the predictive model. The nomogram model can be employed to predict the prognosis of patients with AAV-ILD. Moreover, the model performance is satisfactory. In the future, external datasets could be utilized for external validation.


Assuntos
Anilidas , Vasculite Associada a Anticorpo Anticitoplasma de Neutrófilos , Doenças Pulmonares Intersticiais , Humanos , Vasculite Associada a Anticorpo Anticitoplasma de Neutrófilos/complicações , Nomogramas , Doenças Pulmonares Intersticiais/diagnóstico , China/epidemiologia
11.
J Cancer Res Clin Oncol ; 150(2): 88, 2024 Feb 10.
Artigo em Inglês | MEDLINE | ID: mdl-38341398

RESUMO

PURPOSE: To explore the effect of microtubule-associated protein 4 (MAP4) on lung adenocarcinoma cells in vitro and evaluate its prognostic value. Radioresistance, indicated by reduced efficiency of radiotherapy, is a key factor in treatment failure in lung adenocarcinoma (LADC). This study aims to explore the primary mechanism underlying the relationship between MAP4 and radiation resistance in lung adenocarcinoma. METHODS: We analysed the expression of MAP4 in lung adenocarcinoma by real-time quantitative polymerase chain reaction (RT‒qPCR), immunohistochemistry (IHC) and bioinformatics online databases, evaluated the prognostic value of MAP4 in lung adenocarcinoma and studied its relationship with clinicopathological parameters. Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis identified independent prognostic factors associated with lung adenocarcinoma that were used to construct a nomogram, internal validation was performed. We then evaluated the accuracy and clinical validity of the model using a receiver operating characteristic (ROC) curve, time-dependent C-index analysis, a calibration curve, and decision curve analysis (DCA). Scratch assays and transwell assays were used to explore the effect of MAP4 on the migration and invasion of lung adenocarcinoma cells. Bioinformatics analysis, RT‒qPCR, Cell Counting Kit-8 (CCK-8) assays and Western blot experiments were used to study the relationship between MAP4, epithelial-mesenchymal transition (EMT) and radiation resistance in lung adenocarcinoma. RESULTS: MAP4 expression in lung adenocarcinoma tissues was significantly higher than that in adjacent normal lung tissues. High expression of MAP4 is associated with poorer overall survival (OS) in patients with lung adenocarcinoma. Univariate Cox regression analysis showed that pT stage, pN stage, TNM stage and MAP4 expression level were significantly associated with poorer OS in LADC patients. Multivariate Cox regression analysis and LASSO regression analysis showed that only the pT stage and MAP4 expression level were associated with LADC prognosis. The nomogram constructed based on the pT stage and MAP4 expression showed good predictive accuracy. ROC curves, corrected C-index values, calibration curves, and DCA results showed that the nomogram performed well in both the training and validation cohorts and had strong clinical applicability. The results of in vitro experiments showed that the downregulation of MAP4 significantly affected the migration and invasion of lung adenocarcinoma cells. MAP4 was strongly correlated with EMT-related markers. Further studies suggested that the downregulation of MAP4 can affect the viability of lung adenocarcinoma cells after irradiation and participate in the radiation resistance of lung adenocarcinoma cells by affecting EMT. CONCLUSION: MAP4 is highly expressed in lung adenocarcinoma; it may affect prognosis by promoting the migration and invasion of cancer cells. We developed a nomogram including clinical factors and MAP4 expression that can be used for prognosis prediction in patients with lung adenocarcinoma. MAP4 participates in radiation resistance in lung adenocarcinoma by regulating the radiation-induced EMT process. MAP4 may serve as a biomarker for lung adenocarcinoma prognosis evaluation and as a new target for improving radiosensitivity.


Assuntos
Adenocarcinoma de Pulmão , Neoplasias Pulmonares , Tolerância a Radiação , Humanos , Adenocarcinoma de Pulmão/genética , Adenocarcinoma de Pulmão/radioterapia , Transição Epitelial-Mesenquimal/genética , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/radioterapia , Proteínas Associadas aos Microtúbulos , Nomogramas , Oncogenes , Prognóstico
12.
Sci Rep ; 14(1): 3470, 2024 02 12.
Artigo em Inglês | MEDLINE | ID: mdl-38342950

RESUMO

Microvascular invasion (MVI) is a critical risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). This study aimed to firstly develop and validate nomograms based on MVI grade for predicting recurrence, especially early recurrence, and overall survival in patients with early-stage HCC after curative resection. We retrospectively reviewed the data of patients with early-stage HCC who underwent curative hepatectomy in the First Affiliated Hospital of Fujian Medical University (FHFU) and Mengchao Hepatobiliary Hospital of Fujian Medical University (MHH). Kaplan-Meier curves and Cox proportional hazards regression models were used to analyse disease-free survival (DFS) and overall survival (OS). Nomogram models were constructed on the datasets from the 70% samples of and FHFU, which were validated using bootstrap resampling with 30% samples as internal validation and data of patients from MHH as external validation. A total of 703 patients with early-stage HCC were included to create a nomogram for predicting recurrence or metastasis (DFS nomogram) and a nomogram for predicting survival (OS nomogram). The concordance indexes and calibration curves in the training and validation cohorts showed optimal agreement between the predicted and observed DFS and OS rates. The predictive accuracy was significantly better than that of the classic HCC staging systems.


Assuntos
Carcinoma Hepatocelular , Neoplasias Hepáticas , Humanos , Carcinoma Hepatocelular/patologia , Nomogramas , Neoplasias Hepáticas/patologia , Estudos Retrospectivos , Hepatectomia , Prognóstico
13.
Cancer Immunol Immunother ; 73(3): 41, 2024 Feb 13.
Artigo em Inglês | MEDLINE | ID: mdl-38349474

RESUMO

BACKGROUND: The tumor microenvironment (TME) encompasses a variety of cells that influence immune responses and tumor growth, with tumor-associated macrophages (TAM) being a crucial component of the TME. TAM can guide prostate cancer in different directions in response to various external stimuli. METHODS: First, we downloaded prostate cancer single-cell sequencing data and second-generation sequencing data from multiple public databases. From these data, we identified characteristic genes associated with TAM clusters. We then employed machine learning techniques to select the most accurate TAM gene set and developed a TAM-related risk label for prostate cancer. We analyzed the tumor-relatedness of the TAM-related risk label and different risk groups within the population. Finally, we validated the accuracy of the prognostic label using single-cell sequencing data, qPCR, and WB assays, among other methods. RESULTS: In this study, the TAM_2 cell cluster has been identified as promoting the progression of prostate cancer, possibly representing M2 macrophages. The 9 TAM feature genes selected through ten machine learning methods and demonstrated their effectiveness in predicting the progression of prostate cancer patients. Additionally, we have linked these TAM feature genes to clinical pathological characteristics, allowing us to construct a nomogram. This nomogram provides clinical practitioners with a quantitative tool for assessing the prognosis of prostate cancer patients. CONCLUSION: This study has analyzed the potential relationship between TAM and PCa and established a TAM-related prognostic model. It holds promise as a valuable tool for the management and treatment of PCa patients.


Assuntos
Macrófagos , Neoplasias da Próstata , Masculino , Humanos , Neoplasias da Próstata/genética , Macrófagos Associados a Tumor , Aprendizado de Máquina , Nomogramas , Microambiente Tumoral/genética
14.
Sci Rep ; 14(1): 2861, 2024 02 04.
Artigo em Inglês | MEDLINE | ID: mdl-38311615

RESUMO

Accurately predicting prognosis subcutaneous leiomyosarcoma (LMS) is crucial for guiding treatment decisions in patients. The objective of this study was to develop prediction models for cancer-specific survival (CSS) in patients with subcutaneous LMS. The collected cases of diagnosed subcutaneous LMS were randomly divided into a training cohort and a validation cohort at a 6:4 ratio based on tumor location and histological code. The X-tile program was utilized to determine the optimal cutoff points for age index. Univariate and Cox multivariate regression analyses were conducted to identify independent risk factors for subcutaneous LMS patients. Nomograms were constructed to predict CSS, and their performance was assessed using C-index and calibration plots. Additionally, a decision tree model was established using recursive partitioning analysis to determine the total score for CSS prediction in subcutaneous LMS patients based on the nomogram model. A total of 1793 patients with subcutaneous LMS were found. X-tile software divides all patients into ≤ 61 years old, 61-82 years old, and ≥ 82 years old. The most important anatomical sites were the limbs (including the upper and lower limbs, 48.0%). Only 6.2% of patients received chemotherapy, while 44% had a history of radiotherapy and 92.9% underwent surgery. The independent risk factors for patients with subcutaneous LMS were age, summary stage, grade, and surgery. CSS was significantly decreased in patients with distant metastases, which showed the highest independent risk predictor (HR 4.325, 95% CI 3.010-6.214, p < 0.001). The nomogram prediction model of LMS was constructed based on four risk factors. The C-index for this model was 0.802 [95% CI 0.781-0.823] and 0.798 [95% CI 0.768-0.829]. The training cohort's 3-, 5-, and 10-year AUCs for CSS in patients with subcutaneous LMS were 0.833, 0.830, and 0.859, and the validation cohort's AUC for predicting CSS rate were 0.849, 0.830, and 0.803, respectively. Recursive segmentation analysis divided patients into 4 risk subgroups according to the total score in the nomogram, including low-risk group < 145, intermediate-low-risk group ≥ 145 < 176, intermediate-high-risk group ≥ 176 < 196, and high-risk group ≥ 196; The probability of the four risk subgroups is 9.1%, 34%, 49%, and 79% respectively. In this retrospective study, a novel nomogram or corresponding risk classification system for patients with subcutaneous LMS were developed, which may assist clinicians in identifying high-risk patients and in guiding the clinical decision.


Assuntos
Compostos de Anilina , Leiomiossarcoma , Nomogramas , Humanos , Pessoa de Meia-Idade , Idoso , Idoso de 80 Anos ou mais , Estudos Retrospectivos , Extremidade Inferior , Programa de SEER , Prognóstico
15.
Br J Radiol ; 97(1154): 439-450, 2024 Feb 02.
Artigo em Inglês | MEDLINE | ID: mdl-38308028

RESUMO

OBJECTIVES: Accurate axillary evaluation plays an important role in prognosis and treatment planning for breast cancer. This study aimed to develop and validate a dynamic contrast-enhanced (DCE)-MRI-based radiomics model for preoperative evaluation of axillary lymph node (ALN) status in early-stage breast cancer. METHODS: A total of 410 patients with pathologically confirmed early-stage invasive breast cancer (training cohort, N = 286; validation cohort, N = 124) from June 2018 to August 2022 were retrospectively recruited. Radiomics features were derived from the second phase of DCE-MRI images for each patient. ALN status-related features were obtained, and a radiomics signature was constructed using SelectKBest and least absolute shrinkage and selection operator regression. Logistic regression was applied to build a combined model and corresponding nomogram incorporating the radiomics score (Rad-score) with clinical predictors. The predictive performance of the nomogram was evaluated using receiver operator characteristic (ROC) curve analysis and calibration curves. RESULTS: Fourteen radiomic features were selected to construct the radiomics signature. The Rad-score, MRI-reported ALN status, BI-RADS category, and tumour size were independent predictors of ALN status and were incorporated into the combined model. The nomogram showed good calibration and favourable performance for discriminating metastatic ALNs (N + (≥1)) from non-metastatic ALNs (N0) and metastatic ALNs with heavy burden (N + (≥3)) from low burden (N + (1-2)), with the area under the ROC curve values of 0.877 and 0.879 in the training cohort and 0.859 and 0.881 in the validation cohort, respectively. CONCLUSIONS: The DCE-MRI-based radiomics nomogram could serve as a potential non-invasive technique for accurate preoperative evaluation of ALN burden, thereby assisting physicians in the personalized axillary treatment for early-stage breast cancer patients. ADVANCES IN KNOWLEDGE: This study developed a potential surrogate of preoperative accurate evaluation of ALN status, which is non-invasive and easy-to-use.


Assuntos
Neoplasias da Mama , Humanos , Feminino , Neoplasias da Mama/patologia , Estudos Retrospectivos , Metástase Linfática/diagnóstico por imagem , Metástase Linfática/patologia , Estudos de Viabilidade , Linfonodos/diagnóstico por imagem , Linfonodos/patologia , Nomogramas , Imageamento por Ressonância Magnética/métodos
16.
J Cardiothorac Surg ; 19(1): 39, 2024 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-38303053

RESUMO

BACKGROUND: Identification of micropapillary and solid subtypes components in small-sized (≤ 2 cm) lung adenocarcinoma plays a crucial role in determining optimal surgical procedures. This study aims to propose a straightforward prediction method utilizing preoperative available indicators. METHODS: From January 2019 to July 2022, 341 consecutive patients with small-sized lung adenocarcinoma who underwent curative resection in thoracic surgery department of Xuanwu Hospital, Capital Medical University were retrospectively analyzed. The patients were divided into two groups based on whether solid or micropapillary components ≥ 5% or not (S/MP5+ and S/MP5-). Univariate analysis and multivariate logistic regression analysis were utilized to identify independent predictors of S/MP5+. Then a nomogram was constructed to intuitively show the results. Finally, the calibration curve with a 1000 bootstrap resampling and the receiver operating characteristic (ROC) curve were depicted to evaluate its performance. RESULTS: According to postoperative pathological results, 79 (23.2%) patients were confirmed as S/MP5+ while 262 (76.8%) patients were S/MP5-. Based on multivariate analysis, maximum diameter (p = 0.010), consolidation tumor ratio (CTR) (p < 0.001) and systemic immune-inflammation index (SII) (p < 0.001) were identified as three independent risk factors and incorporated into the nomogram. The calibration curve showed good concordance between the predicted and actual probability of S/MP5+. Besides, the model showed certain discrimination, with an area under ROC curve of 0.893. CONCLUSIONS: The model constructed based on SII is a practical tool to predict high-grade subtypes components of small-sized lung adenocarcinoma preoperatively and contribute to determine the optimal surgical approach.


Assuntos
Adenocarcinoma de Pulmão , Neoplasias Pulmonares , Humanos , Estudos Retrospectivos , Adenocarcinoma de Pulmão/cirurgia , Adenocarcinoma de Pulmão/patologia , Nomogramas , Inflamação , Neoplasias Pulmonares/cirurgia , Neoplasias Pulmonares/patologia
17.
Front Immunol ; 15: 1323151, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38298193

RESUMO

Introduction: Identifying which patient may benefit from immunotherapeutic early-phase clinical trials is an unmet need in drug development. Among several proposed prognostic scores, none has been validated in patients receiving immunomodulating agents (IMAs)-based combinations. Patients and methods: We retrospectively collected data of 208 patients enrolled in early-phase clinical trials investigating IMAs at our Institution, correlating clinical and blood-based variables with overall survival (OS). A retrospective cohort of 50 patients treated with IMAs at Imperial College (Hammersmith Hospital, London, UK) was used for validation. Results: A total of 173 subjects were selected for analyses. Most frequent cancers included non-small cell lung cancer (26%), hepatocellular carcinoma (21.5%) and glioblastoma (13%). Multivariate analysis (MVA) revealed 3 factors to be independently associated with OS: line of treatment (second and third vs subsequent, HR 0.61, 95% CI 0.40-0.93, p 0.02), serum albumin as continuous variable (HR 0.57, 95% CI 0.36-0.91, p 0.02) and number of metastatic sites (<3 vs ≥3, HR 0.68, 95% CI 0.48-0.98, p 0.04). After splitting albumin value at the median (3.84 g/dL), a score system was capable of stratifying patients in 3 groups with significantly different OS (p<0.0001). Relationship with OS reproduced in the external cohort (p=0.008). Then, from these factors we built a nomogram. Conclusions: Prior treatment, serum albumin and number of metastatic sites are readily available prognostic traits in patients with advanced malignancies participating into immunotherapy early-phase trials. Combination of these factors can optimize patient selection at study enrollment, maximizing therapeutic intent.


Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Humanos , Prognóstico , Estudos Retrospectivos , Carcinoma Pulmonar de Células não Pequenas/patologia , Nomogramas , Seleção de Pacientes , Neoplasias Pulmonares/patologia , Imunoterapia/efeitos adversos , Albumina Sérica
18.
Eur J Cancer Prev ; 33(2): 105-114, 2024 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-38299664

RESUMO

OBJECTIVES: Adjuvant chemotherapy benefits in elderly patients with stage II colon cancer (CC) remain controversial. We aimed to construct a nomogram to estimate the chemotherapy survival benefits in elderly patients. METHODS: The training and testing cohort were patients with stage II CC older than 70 years from the Surveillance, Epidemiology, and End Results (SEER) database, while the external validation cohort included patients from the National Cancer Center (NCC). Cox proportional hazard models were used to determine the covariates associated with overall survival (OS). Using the risk factors identified by Cox proportional hazards regression, a nomogram was developed to predict OS. Nomogram precision was assessed using receiver operating characteristic and calibration curves. RESULTS: The present study recruited 42 097 and 504 patients from the SEER database and NCC, respectively. The OS of patients who underwent surgery plus adjuvant chemotherapy was considerably longer than patients who underwent surgery alone. The nomogram included variables related to OS, including age, year of diagnosis, sex, AJCC T stage, tumor location, tumor size, harvested lymph nodes, and chemotherapy. According to the nomogram score, the elderly patients were separated into high- and low-risk groups, with high-risk group nomogram scores being greater than the median value, and vice versa. Patients in the high-risk group witnessed worse prognosis and were more likely to benefit from postoperative chemotherapy. CONCLUSION: This nomogram can be regarded as a useful clinical tool for assessing the potential adjuvant chemotherapy benefits and for predicting survival in elderly patients with stage II CC.


Assuntos
Neoplasias do Colo , Nomogramas , Idoso , Humanos , Prognóstico , Quimioterapia Adjuvante , Neoplasias do Colo/diagnóstico , Neoplasias do Colo/tratamento farmacológico , Neoplasias do Colo/epidemiologia , Bases de Dados Factuais
19.
Beijing Da Xue Xue Bao Yi Xue Ban ; 56(1): 120-130, 2024 Feb 18.
Artigo em Chinês | MEDLINE | ID: mdl-38318906

RESUMO

OBJECTIVE: To evaluate the prognostic significance of inflammatory biomarkers, prognostic nutritional index and clinicopathological characteristics in tongue squamous cell carcinoma (TSCC) patients who underwent cervical dissection. METHODS: The retrospective cohort study consisted of 297 patients undergoing tumor resection for TSCC between January 2017 and July 2018. The study population was divided into the training set and validation set by 7 :3 randomly. The peripheral blood indices of interest were preoperative neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), systemic inflammation score (SIS) and prognostic nutritional index (PNI). Kaplan-Meier survival analysis and multivariable Cox regression analysis were used to evaluate independent prognostic factors for overall survival (OS) and disease-specific survival (DSS). The nomogram's accuracy was internally validated using concordance index, receiver operating characteristic (ROC) curve, area under the curve (AUC), calibration plot and decision curve analysis. RESULTS: According to the univariate Cox regression analysis, clinical TNM stage, clinical T category, clinical N category, differentiation grade, depth of invasion (DOI), tumor size and pre-treatment PNI were the prognostic factors of TSCC. Multivariate Cox regression analysis revealed that pre-treatment PNI, clinical N category, DOI and tumor size were independent prognostic factors for OS or DSS (P < 0.05). Positive neck nodal status (N≥1), PNI≤50.65 and DOI > 2.4 cm were associated with the poorer 5-year OS, while a positive neck nodal status (N≥1), PNI≤50.65 and tumor size > 3.4 cm were associated with poorer 5-year DSS. The concordance index of the nomograms based on independent prognostic factors was 0.708 (95%CI, 0.625-0.791) for OS and 0.717 (95%CI, 0.600-0.834) for DSS. The C-indexes for external validation of OS and DSS were 0.659 (95%CI, 0.550-0.767) and 0.780 (95%CI, 0.669-0.890), respectively. The 1-, 3- and 5-year time-dependent ROC analyses (AUC = 0.66, 0.71 and 0.72, and AUC = 0.68, 0.77 and 0.79, respectively) of the nomogram for the OS and DSS pronounced robust discriminative ability of the model. The calibration curves showed good agreement between the predicted and actual observations of OS and DSS, while the decision curve confirmed its pronounced application value. CONCLUSION: Pre-treatment PNI, clinical N category, DOI and tumor size can potentially be used to predict OS and DSS of patients with TSCC. The prognostic nomogram based on these variables exhibited good accurary in predicting OS and DSS in patients with TSCC who underwent cervical dissection. They are effective tools for predicting survival and helps to choose appropriate treatment strategies to improve the prognosis.


Assuntos
Carcinoma de Células Escamosas , Neoplasias da Língua , Humanos , Prognóstico , Nomogramas , Carcinoma de Células Escamosas/cirurgia , Carcinoma de Células Escamosas/patologia , Estudos Retrospectivos , Neoplasias da Língua/cirurgia , Inflamação , Língua/patologia
20.
BMC Cancer ; 24(1): 212, 2024 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-38360582

RESUMO

OBJECTIVE: To screen the risk factors affecting the recurrence risk of patients with ampullary carcinoma (AC)after radical resection, and then to construct a model for risk prediction based on Lasso-Cox regression and visualize it. METHODS: Clinical data were collected from 162 patients that received pancreaticoduodenectomy treatment in Hebei Provincial Cancer Hospital from January 2011 to January 2022. Lasso regression was used in the training group to screen the risk factors for recurrence. The Lasso-Cox regression and Random Survival Forest (RSF) models were compared using Delong test to determine the optimum model based on the risk factors. Finally, the selected model was validated using clinical data from the validation group. RESULTS: The patients were split into two groups, with a 7:3 ratio for training and validation. The variables screened by Lasso regression, such as CA19-9/GGT, AJCC 8th edition TNM staging, Lymph node invasion, Differentiation, Tumor size, CA19-9, Gender, GPR, PLR, Drinking history, and Complications, were used in modeling with the Lasso-Cox regression model (C-index = 0.845) and RSF model (C-index = 0.719) in the training group. According to the Delong test we chose the Lasso-Cox regression model (P = 0.019) and validated its performance with time-dependent receiver operating characteristics curves(tdROC), calibration curves, and decision curve analysis (DCA). The areas under the tdROC curves for 1, 3, and 5 years were 0.855, 0.888, and 0.924 in the training group and 0.841, 0.871, and 0.901 in the validation group, respectively. The calibration curves performed well, as well as the DCA showed higher net returns and a broader range of threshold probabilities using the predictive model. A nomogram visualization is used to display the results of the selected model. CONCLUSION: The study established a nomogram based on the Lasso-Cox regression model for predicting recurrence in AC patients. Compared to a nomogram built via other methods, this one is more robust and accurate.


Assuntos
Ampola Hepatopancreática , Nomogramas , Humanos , Ampola Hepatopancreática/cirurgia , Antígeno CA-19-9 , Pancreaticoduodenectomia , Fatores de Risco
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