Development and validation of nomogram based on SIRI for predicting the clinical outcome in patients with nasopharyngeal carcinomas

The Systemic Inflammation Response Index (SIRI), based on peripheral lymphocyte, neutrophil, and monocyte counts, was recently investigated as a prognostic marker for several tumors. However, use of the SIRI has not been reported for nasopharyngeal carcinoma (NPC). We evaluated the prognostic value of the SIRI in primary and validation cohorts. We also established an effective prognostic nomogram for NPC based on clinicopathological parameters and the SIRI. The predictive accuracy and discriminative ability of the nomogram were determined using the concordance index (C-index) and a calibration curve and were compared with tumor-node-metastasis classifications. Our Kaplan-Meier survival analysis results showed that the SIRI was associated with the overall survival of patients with NPC in the primary and validation cohorts. The SIRI was identified to be an independent prognostic factor for NPC. In addition, we developed and validated a new prognostic nomogram that integrated clinicopathological factors and the SIRI. This nomogram can efficiently predict the prognosis of patients with NPC. The SIRI is a novel, simple and inexpensive prognostic predictor for patients with NPC. The SIRI has important value for predicting the prognosis of patients with NPC and developing individualized treatment plans.

Download Full-text

The “effect” of T classification on colorectal liver metastasis.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.e15049 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. e15049-e15049

Author(s):

Lunpo Wu ◽

Hongjuan Zheng ◽

Jianfei Fu ◽

Jinlin Du ◽

Shu Zheng ◽

...

Keyword(s):

Colorectal Cancer ◽

Lymph Node ◽

Predictive Accuracy ◽

Assessment Model ◽

Discriminative Ability ◽

Cox Models ◽

Tissue Samples ◽

Kaplan Meier ◽

Cox Analysis ◽

T Classification

e15049 Background: T classification is considered as a detail and credible category of the depth of tumor invasion. Generally, with the increasing T category, the risk of metastases should be continuously rising. However, there is a group of metastatic patients with early T classification, who were supposed to have a low metastatic probability. Our study aims to present the T classification on metastatic liver colorectal cancer (CRLM) in both clinical and biological aspects, and explore preoperative predictions to develop a convenient individual assessment model for clinicians to speculate whether these patients, whose prognosis is extremely poor. Methods: Tissue samples of primary colorectal cancer were obtained at our center. Patients with CRLM during 2010 to 2014 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier and Cox models were used to analyze the survival differences. We identified preoperative prognostic factors based on the Cox analysis and constructed a nomogram model. The predictive accuracy and discriminative ability were measured by concordance index (C-index) and calibration curve. Results: The mRNA array from our hospital showed that there is an obvious difference between the T1/2N0M1 subgroup and the T3/4N0M1 subgroup. Patients with early T classification (T1) were more often have tumors located in rectum, with well differentiation, with no lymph node metastasis and a higher CEA level. Further survival analysis indicated that early T classification (T1) was an independent prognostic factor with poorer survival. When the lymph node (N) status was taken into consideration, patients with T1 N+ had an obvious better survival than T1 N0 patients. A clinical nomogram was constructed based on preoperative factors. The calibration curves for probability of 1-, 2-, and 5-year overall survival showed a good agreement between nomogram prediction and actual observation. Conclusions: The prognosis of T1M1 is extremely poorer than T3/4M1. The prognosis of T1N+ is better than T1N0. It is time to pay more attention to the high-risk monitoring and screening of T1 in early colon cancer.

Download Full-text

SATB1 is Correlated with Progression and Metastasis of Breast Cancers: A Meta-Analysis

Cellular Physiology and Biochemistry ◽

10.1159/000445558 ◽

2016 ◽

Vol 38 (5) ◽

pp. 1975-1983 ◽

Cited By ~ 13

Author(s):

Zhongya Pan ◽

Wei Jing ◽

Keli He ◽

Li Zhang ◽

Xinghua Long

Keyword(s):

Meta Analysis ◽

Tumour Size ◽

Cochrane Library ◽

Clinicopathological Parameters ◽

Her2 Status ◽

Breast Cancers ◽

Tumor Node Metastasis ◽

Normal Tissues ◽

Node Metastasis ◽

Potential Marker

Background/Aims: Several researches have evaluated the significance of SATB1 (Special AT-rich sequence binding protein 1) expression in breast cancers (BCs), but the results have been disputed, especially in the aspects of clinicopathological features and prognosis. Therefore, our study aimed to use a meta-analysis to summarize the clinical and prognostic relevance of SATB1 gene expression in BCs. Methods: A literature search of PubMed, EMBASE, Cochrane library, Chinese Wanfang and CNKI was performed to identify eligible studies. Ten studies total, comprising 5,185 patients (1,699 SATB1-positive and 3,486 SATB1-negative), were enrolled in our study, which was performed using Revman5.3 Software and Stata11.0 Software. Results: This meta-analysis showed that the expression of SATB1 was significantly higher in breast cancer than in normal tissues (OR = 12.28; 95%CI = 6.01-25.09), and was statistically related to several clinicopathological parameters, including lymph node metastasis (OR = 1.55, 95%CI = 1.01-2.39) and Tumor Node Metastasis(TNM) stage (OR = 0.35, 95%CI = 0.22-0.56). However, the level of SATB1 was not statistically associated with the age (OR = 1.13, 95%CI = 0.87-1.46), tumour size (OR = 0.72, 95%CI = 0.44-1.19), estrogen receptor (OR = 0.78, 95%CI = 0.55-1.09), progesterone receptor (OR = 0.64, 95%CI = 0.32-1.29), HER2 status (OR=1.98, 95%CI = 0.74-5.30), and histological type (OR = 0.49, 95%CI = 0.22-1.11). Conclusion: High expression of SATB1 was significantly correlated with tumourigenesis and metastasis of BCs, indicating poor prognosis for patients. SATB1 could serve as a potential marker for detection and prognosis evaluation of breast cancers.

Download Full-text

Development and Validation of Multivariate Models Integrating Preoperative Clinicopathological Parameters and Radiographic Findings Based on Late Arterial Phase CT Images for Predicting Lymph Node Metastasis in Gastric Cancer

Academic Radiology ◽

10.1016/j.acra.2021.01.011 ◽

2021 ◽

Author(s):

Song Liu ◽

Xiangmei Qiao ◽

Mengying Xu ◽

Changfeng Ji ◽

Lin Li ◽

...

Keyword(s):

Gastric Cancer ◽

Lymph Node ◽

Lymph Node Metastasis ◽

Ct Images ◽

Clinicopathological Parameters ◽

Arterial Phase ◽

Multivariate Models ◽

Radiographic Findings ◽

Node Metastasis ◽

Development And Validation

Download Full-text

HIGH RATIO OF EARLY POSTOPERATIVE CALCITONIN TO PREOPERATIVE CALCITONIN COULD BE A NOVEL INDICATOR OF POOR PROGNOSIS IN PATIENTS WITH BIOCHEMICAL INCOMPLETE RESPONSES IN SPORADIC MEDULLARY THYROID CANCER

Endocrine Practice ◽

10.4158/ep-2019-0404 ◽

2020 ◽

Vol 26 (7) ◽

pp. 738-747

Author(s):

Lili Chen ◽

Wenyu Sun ◽

Kai Qian ◽

Kai Guo ◽

Tuanqi Sun ◽

...

Keyword(s):

Thyroid Cancer ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Medullary Thyroid Cancer ◽

Hazard Ratio ◽

Tumor Node Metastasis ◽

Medullary Thyroid ◽

Persistent Disease ◽

Node Metastasis ◽

Kaplan Meier

Objective: In a cohort of medullary thyroid cancer (MTC) patients with biochemical incomplete responses, 37 to 48% developed structural persistent disease; however, few indictors were available to distinguish those patients who were more likely to develop structural disease. We hypothesized that the relationship between preoperative calcitonin (Ctn) and postoperative Ctn (within 3 days after surgery) could be used to predict early prognosis of these patients. Methods: A total of 92 sporadic MTC patients were enrolled in this study. Our team proposed a novel indicator of structural persistent MTC called the calcitonin ratio (CR; CR = postoperative Ctn/preoperative Ctn). Cox regression models and the Kaplan-Meier method were used to evaluate the prognostic capability of CR. The area under the time-dependent receiver-operating characteristic curves (AUC) and the Harrell concordance index (C-index) were used for analysis. Results: The cutoff CR value used to determine MTC prognosis was 0.15. Multivariate Cox analysis revealed that CR (hazard ratio [HR]: 22.974, 95% confidence interval [CI]: 3.259 to 161.959, P = .002), tumor-node-metastasis (HR: 3.968, 95% CI: 1.360 to 21.857; P = .031), and multifocality (HR: 8.466, 95% CI: 1.286 to 55.716; P = .026) independently correlated with MTC prognosis. Kaplan-Meier survival curves demonstrated a lower proportion with structural persistent disease in patients with CR <0.15 ( P<.001). The 3, 5, and 10-year AUC values were 0.798, 0.752, and 0.743, respectively. The C-index of CR was 0.788 (95% CI: 0.763 to 0.813). Conclusion: In this study, CR was identified as a sensitive and specific risk stratification marker for patients with biochemical incomplete responses in sporadic MTC. Abbreviations: ATA = American Thyroid Association; AUC = area under curve; CEA = carcinoembryonic antigen; CR = calcitonin ratio; Ctn = calcitonin; HR = hazard ratio; MTC = medullary thyroid cancer; ROC = receiver operating characteristic; TNM = tumor-node-metastasis

Download Full-text

Preoperative anaemia and thrombocytosis predict adverse prognosis in non‐metastatic renal cell carcinoma with tumour thrombus

BMC Urology ◽

10.1186/s12894-021-00796-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Ruotao Xiao ◽

Chuxiao Xu ◽

Wei He ◽

Lei Liu ◽

Hongxian Zhang ◽

...

Keyword(s):

Risk Factors ◽

Prognostic Factors ◽

Predictive Accuracy ◽

Blood Parameters ◽

Tumour Thrombus ◽

Factors Associated ◽

Node Metastasis ◽

Kaplan Meier ◽

Metastatic Rcc ◽

Preoperative Anaemia

Abstract Background This study aimed to determine the prognostic value of preoperative blood parameters in renal cell carcinoma (RCC) and tumour thrombus (TT) patients that were surgically treated. Method We retrospectively analysed clinicopathological data and blood parameters of 146 RCC and TT patients that were surgically treated. Univariate or multivariate Cox regression analyses were performed to determine the risk factors associated with progression-free survival (PFS) and overall survival (OS). Kaplan-Meier analysis and logistic regression were performed to study the risk factors. Receiver operating characteristic curves were applied to test improvements in the predictive accuracy of the established prognosis score. Results On univariate and multivariate analysis, anaemia (HR 2.873, P = 0.008) and lymph node metastasis (HR 4.811, P = 0.015) were independent prognostic factors linked to OS. Besides, thrombocytosis (HR 2.324, P = 0.011), histologic subtype (HR 2.835, P = 0.004), nuclear grade (HR 2.069, P = 0.033), and lymph node metastasis (HR 5.739, P = 0.001) were independent prognostic factors associated with PFS. Kaplan–Meier curves revealed that patients with anaemia exhibited worse OS than those without it (P = 0.0033). Likewise, patients with thrombocytosis showed worse PFS than those without it (P < 0.0001). Adding the anaemia and thrombocytosis to the SSIGN score improved its predictive accuracy related to OS and PFS. Preoperative anaemia was linked to more symptom at presentation (OR 3.348, P = 0.006), longer surgical time (OR 1.005, P = 0.001), more blood loss (OR 1.000, P = 0.018), more transfusion (OR 2.734, P = 0.004), higher thrombus level (OR 4.750, P = 0.004) and higher nuclear grade (OR 3.449, P = 0.001) while thrombocytosis was associated with more symptom at presentation (OR 7.784, P = 0.007). Conclusions Preoperative anaemia and thrombocytosis were adverse prognostic factors in non-metastatic RCC patients with TT. Also, both preoperative anaemia and thrombocytosis can be clinically used for risk stratification of non-metastatic RCC and TT patients.

Download Full-text

A Nomogram based on a Patient-reported Outcomes Measure: Predicting the Risk of Readmission for Patients with Chronic Heart Failure

10.21203/rs.3.rs-20720/v3 ◽

2020 ◽

Author(s):

Qiang Han ◽

Jia Ren ◽

Jing Tian ◽

Hong Yang ◽

Qing Zhang ◽

...

Keyword(s):

Heart Failure ◽

Chronic Heart Failure ◽

Patient Reported Outcomes ◽

Cox Regression ◽

Predictive Accuracy ◽

Measurement Tool ◽

Concordance Index ◽

Discriminative Ability ◽

Cox Regression Analysis ◽

Patient Reported

Abstract Background Health-related quality of life, evaluated by a patient-reported outcomes measure, is an important prognostic marker in patients with chronic heart failure. This study aimed to use PROM to establish an effective readmission nomogram for chronic heart failure. Methods Using patient-reported outcomes measure as a measurement tool, we conducted a readmission nomogram for chronic heart failure on a prospective observational study comprising 454 patients with chronic heart failure hospitalized between May 2017 to January 2020. Concordance index and calibration curve were used to evaluate the discriminative ability and predictive accuracy of the nomogram. A bootstrap resampling method was used for internal validation of results. Results The median follow-up period in the study was 372 days. After a final COX regression analysis, the gender, income, health care, appetite-sleep, anxiety, depression, paranoia, support, and independence were identified and included in the nomogram. The nomogram showed moderate discrimination, with concordance index of 0.737 (95% CI 0.673-0.800). The calibration curves for the probability of readmission for patients with chronic heart failure showed high consistency between the probability, as predicted, and the actual probability. Conclusions This model offers a platform to assess the risk of readmission for different populations with CHF and can assist clinicians with personalized treatment recommendations.

Download Full-text

A Nomogram based on a Patient-reported Outcomes Measure: Predicting the Risk of Readmission for Patients with Chronic Heart Failure

10.21203/rs.3.rs-20720/v2 ◽

2020 ◽

Author(s):

Qiang Han ◽

Jia Ren ◽

Jing Tian ◽

Hong Yang ◽

Qing Zhang ◽

...

Keyword(s):

Heart Failure ◽

Chronic Heart Failure ◽

Patient Reported Outcomes ◽

Cox Regression ◽

Predictive Accuracy ◽

Measurement Tool ◽

Concordance Index ◽

Discriminative Ability ◽

Cox Regression Analysis ◽

Patient Reported

Download Full-text

A Nomogram based on a Patient-reported Outcomes Measure: Predicting the Risk of Readmission for Patients with Chronic Heart Failure

10.21203/rs.3.rs-20720/v1 ◽

2020 ◽

Author(s):

qiang han ◽

Jing Tian ◽

Hong Yang ◽

Qing Zhang ◽

Ruoya Wang ◽

...

Keyword(s):

Heart Failure ◽

Chronic Heart Failure ◽

Patient Reported Outcomes ◽

Cox Regression ◽

Predictive Accuracy ◽

Measurement Tool ◽

Concordance Index ◽

Discriminative Ability ◽

Cox Regression Analysis ◽

Patient Reported

Abstract Background Health-related quality of life, evaluated by a patient-reported outcomes measure, is an important prognostic marker in patients with chronic heart failure. This study aimed to use PROM to establish an effective readmission nomogram for chronic heart failure. Methods Using patient-reported outcomes measure as a measurement tool, we conducted a readmission nomogram for chronic heart failure on a prospective observational study comprising 454 patients with chronic heart failure hospitalized between May 2017 to January 2020. Concordance index and calibration curve were used to evaluate the discriminative ability and predictive accuracy of the nomogram. A bootstrap resampling method was used for internal validation of results. Results The median follow-up period in the study was 197 days. After a final COX regression analysis, the computed gender, income, health care, appetite-sleep, anxiety, depression, paranoia, support, and independence were identified and included in the nomogram. The nomogram showed moderate discrimination, with concordance index of 0.737 (95% CI 0.673-0.800). The calibration curves for the probability of readmission for patients with chronic heart failure showed high consistency between the probability, as predicted, and the actual probability. Conclusions This model offers a platform to assess the risk of readmission for different populations with CHF and can assist clinicians with personalized treatment recommendations.

Download Full-text

NCC-BCBM, a Nomogram Prognostic Model in Breast Cancer Patients with Bone Metastases

10.21203/rs.3.rs-384643/v1 ◽

2021 ◽

Author(s):

Jie Zhai ◽

Qiang Liu ◽

Ping Bai ◽

Zhongzhao Wang ◽

Yi Fang ◽

...

Keyword(s):

Breast Cancer ◽

Bone Metastasis ◽

Cancer Patients ◽

Calibration Curve ◽

Prognostic Model ◽

Predictive Accuracy ◽

Molecular Subtype ◽

Concordance Index ◽

Breast Cancer Patients ◽

Discriminative Ability

Abstract Purpose Accurate prediction tools to facilitate risk stratification and therapeutic strategies for breast cancer patients with bone metastasis (BCBM) are lacking. We constructed and validated a new nomogram prognostic model, named NCC-BCBM, for breast cancer patients with bone metastasis using a large BCBM cohort from the SEER (Surveillance Epidemiology and End Results) database. Patients and Methods Clinical information for 8655 patients diagnosed from 2011 to 2013 was collected to develop the nomogram prognostic model. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C-index) and calibration curve. The model was further validated in an independent cohort of 4634 BCBM patients diagnosed from 2014 to 2015. Results The following clinical variables were enrolled in the final prognostic model: age, race, surgery, radiation therapy, chemotherapy, laterality, grade, molecular subtype, American Joint Committee on Cancer (AJCC T) stage, AJCC N stage and extra metastatic sites except bone. The C-index for the developed model in training cohort was 0.702 (95% CI, 0.696 to 0.709). The calibration curve for probability of 1-year, 3-year and 5-year survival showed good agreement between prediction by nomogram and direct observation. The prognostic model was validated in an independent validation cohort with a concordance index of 0.748 (95% CI, 0.737 to 0.759). Conclusion We developed and validated a nomogram prognostic model for BCBM patients and the proposed nomogram resulted in good performance.

Download Full-text

A nomogram prediction model for lymph node metastasis in endometrial cancer patients

BMC Cancer ◽

10.1186/s12885-021-08466-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Zhiling Wang ◽

Shuo Zhang ◽

Yifei Ma ◽

Wenhui Li ◽

Jiguang Tian ◽

...

Keyword(s):

Logistic Regression ◽

Endometrial Cancer ◽

Lymph Node ◽

Lymph Node Metastasis ◽

External Validation ◽

Clinicopathological Parameters ◽

Bootstrap Sample ◽

Multivariate Logistic Regression ◽

Node Metastasis ◽

Increased Risk

Abstract Background This study aimed to explore the risk factors for lymph node metastasis (LNM) in patients with endometrial cancer (EC) and develop a clinically useful nomogram based on clinicopathological parameters to predict it. Methods Clinical information of patients who underwent staging surgery for EC was abstracted from Qilu Hospital of Shandong University from January 1st, 2005 to June 31st, 2019. Parameters including patient-related, tumor-related, and preoperative hematologic examination-related were analyzed by univariate and multivariate logistic regression to determine the correlation with LNM. A nomogram based on the multivariate results was constructed and underwent internal and external validation to predict the probability of LNM. Results The overall data from the 1517 patients who met the inclusion criteria were analyzed. 105(6.29%) patients had LNM. According the univariate analysis and multivariate logistic regression analysis, LVSI is the most predictive factor for LNM, patients with positive LVSI had 13.156-fold increased risk for LNM (95%CI:6.834–25.324; P < 0.001). The nomogram was constructed and incorporated valuable parameters including histological type, histological grade, depth of myometrial invasion, LVSI, cervical involvement, parametrial involvement, and HGB levels from training set. The nomogram was cross-validated internally by the 1000 bootstrap sample and showed good discrimination accuracy. The c-index for internal and external validation of the nomogram are 0.916(95%CI:0.849–0.982) and 0.873(95%CI:0.776–0.970), respectively. Conclusions We developed and validated a 7-variable nomogram with a high concordance probability to predict the risk of LNM in patients with EC.

Download Full-text