Incidence trends and survival prediction of urothelial cancer of the bladder: a population-based study

Abstract Background The aim of this study is to determine the incidence trends of urothelial cancer of the bladder (UCB) and to develop a nomogram for predicting the cancer-specific survival (CSS) of postsurgery UCB at a population-based level based on the SEER database. Methods The age-adjusted incidence of UCB diagnosed from 1975 to 2016 was extracted, and its annual percentage change was calculated and joinpoint regression analysis was performed. A nomogram was constructed for predicting the CSS in individual cases based on independent predictors. The predictive performance of the nomogram was evaluated using the consistency index (C-index), net reclassification index (NRI), integrated discrimination improvement (IDI), a calibration plot and the receiver operating characteristics (ROC) curve. Results The incidence of UCB showed a trend of first increasing and then decreasing from 1975 to 2016. However, the overall incidence increased over that time period. The age at diagnosis, ethnic group, insurance status, marital status, differentiated grade, AJCC stage, regional lymph nodes removed status, chemotherapy status, and tumor size were independent prognostic factors for postsurgery UCB. The nomogram constructed based on these independent factors performed well, with a C-index of 0.823 and a close fit to the calibration curve. Its prediction ability for CSS of postsurgery UCB is better than that of the existing AJCC system, with NRI and IDI values greater than 0 and ROC curves exhibiting good performance for 3, 5, and 8 years of follow-up. Conclusions The nomogram constructed in this study might be suitable for clinical use in improving the clinical predictive accuracy of the long-term survival for postsurgery UCB.

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Incidence Trends and Survival Prediction of Urothelial Cancer of the Bladder: A Population-Based Study

10.21203/rs.3.rs-225866/v1 ◽

2021 ◽

Author(s):

Hairong He ◽

Tianjie Liu ◽

Didi Han ◽

Chengzhuo Li ◽

Fengshuo Xu ◽

...

Keyword(s):

Urothelial Cancer ◽

Predictive Accuracy ◽

Population Based ◽

Calibration Plot ◽

Survival Prediction ◽

Operating Characteristics ◽

Prediction Ability ◽

Term Survival ◽

Incidence Trends ◽

Cancer Of The Bladder

Abstract Background. The aim of this study is to determine the incidence trends of urothelial cancer of the bladder (UCB) and to develop a nomogram for predicting the cancer-specific survival (CSS) of postsurgery UCB at a population-based level based on the SEER database. Methods. The age-adjusted incidence of UCB diagnosed from 1975 to 2016 was extracted, and its annual percentage change was calculated and joinpoint regression analysis was performed. A nomogram was constructed for predicting the CSS in individual cases based on independent predictors. The predictive performance of the nomogram was evaluated using the consistency index (C-index), net reclassification index (NRI), integrated discrimination improvement (IDI), a calibration plot and the receiver operating characteristics (ROC) curve. Results. The incidence of UCB showed a trend of first increasing and then decreasing from 1975 to 2016. However, the overall incidence increased over that time period. The age at diagnosis, race, insurance status, marital status, differentiated grade, AJCC stage, regional lymph nodes removed status, chemotherapy status and tumor size were independent prognostic factors for postsurgery UCB. The nomogram constructed based on these independent factors performed well, with a C-index of 0.823 and a close fit to the calibration curve. Its prediction ability for CSS of postsurgery UCB is better than that of the existing AJCC system, with NRI and IDI values greater than 0 and ROC curves exhibiting good performance for 3, 5, and 8 years of follow-up. Conclusions. The nomogram constructed in this study might be suitable for clinical use in improving the clinical predictive accuracy of the long-term survival for postsurgery UCB.

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Relationship between Clinicopathologic Variables in Breast Cancer Overall Survival Using Biogeography-Based Optimization Algorithm

BioMed Research International ◽

10.1155/2019/2304128 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12

Author(s):

Li-Yeh Chuang ◽

Guang-Yu Chen ◽

Sin-Hua Moi ◽

Fu Ou-Yang ◽

Ming-Feng Hou ◽

...

Keyword(s):

Breast Cancer ◽

Overall Survival ◽

Predictive Accuracy ◽

Cancer Prognosis ◽

University Hospital ◽

Health Concern ◽

Survival Models ◽

Survival Prediction ◽

Prediction Ability ◽

Minimum Number

Breast cancer is the most common cancer among women and is considered a major public health concern worldwide. Biogeography-based optimization (BBO) is a novel metaheuristic algorithm. This study analyzed the relationship between the clinicopathologic variables of breast cancer using Cox proportional hazard (PH) regression on the basis of the BBO algorithm. The dataset is prospectively maintained by the Division of Breast Surgery at Kaohsiung Medical University Hospital. A total of 1896 patients with breast cancer were included and tracked from 2005 to 2017. Fifteen general breast cancer clinicopathologic variables were collected. We used the BBO algorithm to select the clinicopathologic variables that could potentially contribute to predicting breast cancer prognosis. Subsequently, Cox PH regression analysis was used to demonstrate the association between overall survival and the selected clinicopathologic variables. C-statistics were used to test predictive accuracy and the concordance of various survival models. The BBO-selected clinicopathologic variables model obtained the highest C-statistic value (80%) for predicting the overall survival of patients with breast cancer. The selected clinicopathologic variables included tumor size (hazard ratio [HR] 2.372, p = 0.006), lymph node metastasis (HR 1.301, p = 0.038), lymphovascular invasion (HR 1.606, p = 0.096), perineural invasion (HR 1.546, p = 0.168), dermal invasion (HR 1.548, p = 0.028), total mastectomy (HR 1.633, p = 0.092), without hormone therapy (HR 2.178, p = 0.003), and without chemotherapy (HR 1.234, p = 0.491). This number was the minimum number of discriminators required for optimal discrimination in the breast cancer overall survival model with acceptable prediction ability. Therefore, on the basis of the clinicopathologic variables, the survival prediction model in this study could contribute to breast cancer follow-up and management.

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Preoperative lymphocyte-to-monocyte ratio improves the prediction of survival outcomes after radical cystectomy for bladder cancer

10.21203/rs.3.rs-20874/v1 ◽

2020 ◽

Author(s):

Hai Bi ◽

Ye Yan ◽

Zijian Qin ◽

Guoliang Wang ◽

Lulin Ma ◽

...

Keyword(s):

Bladder Cancer ◽

Radical Cystectomy ◽

Clinical Decision Making ◽

Cox Regression ◽

Predictive Accuracy ◽

Prognostic Significance ◽

Survival Outcomes ◽

Operating Characteristics ◽

Net Benefit ◽

Term Survival

Abstract Purpose To determine the prognostic significance of preoperative lymphocyte-to-monocyte (LMR) in bladder cancer (BCa) patients undergoing radical cystectomy (RC), and to validate the prognostic benefit provided by LMR compared to the models relying on the clinicopathological factors alone. Materials and Methods Retrospective analysis of the 342 BCa patients undergoing RC at our institution from 2004 to 2017 was performed to evaluate the prognostic significance of the LMR. Overall survival (OS) and cancer-specific survival (CSS) was assessed by the Kaplan-Meier method. Cox regression models identified risk factors for survival outcomes. Two nomograms were developed based on the basal models to predict the OS and CSS at 1, 3 and 5 years after RC. The accuracy of the nomograms was assessed with receiver operating characteristics (ROC) curves and concordance-index. Decision curve analyses (DCA) were performed to identify the net benefit by the nomograms. Results Excellent long-term survival outcomes of patients were associated with higher LMR level patients. The median survival time for higher LMR level patients was 98.8 months in OS and over 120 months in CSS. In Cox regression multivariate analysis, preoperative LMR, as a continuous variable, is an independent survival outcome predictor ( p <0.001). The addition of LMR to standard model significantly improved its discrimination for prediction of OS by 5.8% and CSS by 5.4% (both p <0.001). Moreover, as shown in DCA, the use of the nomogram including LMR would incur a net benefit over the base models for predicting OS and CSS at 1, 3 and 5 years. Conclusions Elevated preoperative LMR among BCa patients undergoing RC is independently associated with significantly better OS and CSS. Moreover, the increase in predictive accuracy after the inclusion of LMR in multiparametric prediction tools is significant. Therefore, LMR may be useful in preoperative patient risk stratification to help patient counseling and clinical decision making.

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Nomogram for Predicting Long-Term Survival after Synchronous Resection for Hepatocellular Carcinoma and Inferior Vena Cava Tumor Thrombosis: A Multicenter Retrospective Study

Journal of Oncology ◽

10.1155/2020/3264079 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Yannan Bai ◽

Jiayi Wu ◽

Yong Zeng ◽

Jie Chen ◽

Shuangjia Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Inferior Vena Cava ◽

Inferior Vena ◽

Cox Regression ◽

Predictive Accuracy ◽

Vena Cava ◽

Calibration Plot ◽

Curative Intent ◽

Term Survival ◽

Tumor Thrombosis

Background. Although surgery for hepatocellular carcinoma (HCC) complicated with inferior vena cava tumor thrombus (IVCTT) may improve survival for some patients, prognostic markers remain elusive because of its rarity. We constructed a prognostic nomogram which predicts individualized survival benefit of curative-intent surgery for HCC patients with IVCTT. Methods. According to abdominothoracic anatomy of inferior vena cava (IVC), IVCTT can be divided into 3 types: inferior diaphragmic (ID), superior diaphragmic (SD), and intracardiac type (IC). Data of 64 HCC patients with IVCTT who underwent curative-intent surgery between 2008 and 2015 in four centers in China were analyzed retrospectively. Univariate and multivariate Cox regression analyses were conducted to select variables for the construction of a prognostic nomogram. Predictive accuracy and discriminative ability were examined by concordance index (C-index) and calibration curve. Results. Of 64 patients in the IVCTT classification, 37 (57.8%) were classified as ID type, 15 (23.4%) as SD type, and 12 (18.8%) as IC type. The 1-, 2-, 3-, and 5-year disease-specific survival (DSS) rates for patients in ID, SD, and IC groups were 94.4%, 55.6%, 71.4%, and 30.0%; 27.8%, 21.4%, 7.1%, and 0%; and 8.3%, 0%, 0%, and 0%, respectively. Independent factors included in the nomogram were ECOG performance status, AFP level ≥ 400 μg/L, tumor size ≥ 10 cm, portal vein tumor thrombosis, and IVCTT classification. The C-index of the nomogram was 0.812 (95% CI 0.761–0.873). The calibration plot for DSS probability showed excellent agreement between the prediction by nomogram and actual observation. Conclusions. Curative-intent surgery should be carefully evaluated and suggested according to our novel IVCTT classification. We have developed a visual web-based nomogram model to predict oncological prognosis of curative-intent surgery for HCC patients with IVCTT.

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Incidence trends and survival prediction of hepatoblastoma in children: a population-based study

Cancer Communications ◽

10.1186/s40880-019-0411-7 ◽

2019 ◽

Vol 39 (1) ◽

pp. 62 ◽

Cited By ~ 9

Author(s):

Jincheng Feng ◽

Georgios Polychronidis ◽

Ulrike Heger ◽

Giovanni Frongia ◽

Arianeb Mehrabi ◽

...

Keyword(s):

Population Based ◽

Survival Prediction ◽

Population Based Study ◽

Incidence Trends

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Faculty Opinions recommendation of Long-term survival in amyotrophic lateral sclerosis: a population-based study.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718225859.793529738 ◽

2017 ◽

Author(s):

Ammar Al-Chalabi

Keyword(s):

Amyotrophic Lateral Sclerosis ◽

Population Based ◽

Term Survival ◽

Population Based Study ◽

Long Term Survival ◽

Lateral Sclerosis

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Comparing the characteristics and predicting the survival of patients with head and neck melanoma versus body melanoma: a population-based study

BMC Cancer ◽

10.1186/s12885-021-08105-y ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yuxin Ding ◽

Runyi Jiang ◽

Yuhong Chen ◽

Jing Jing ◽

Xiaoshuang Yang ◽

...

Keyword(s):

Head And Neck ◽

Health Management ◽

External Validation ◽

Area Under The Curve ◽

Population Based ◽

Survival Prediction ◽

Cancer Specific Survival ◽

Cox Models ◽

Lentigo Maligna Melanoma ◽

Clinical Tools

Abstract Background Previous studies reported cutaneous melanoma in head and neck (HNM) differed from those in other regions (body melanoma, BM). Individualized tools to predict the survival of patients with HNM or BM remain insufficient. We aimed at comparing the characteristics of HNM and BM, developing and validating nomograms for predicting the survival of patients with HNM or BM. Methods The information of patients with HNM or BM from 2004 to 2015 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The HNM group and BM group were randomly divided into training and validation cohorts. We used the Kaplan-Meier method and multivariate Cox models to identify independent prognostic factors. Nomograms were developed via the rms and dynnom packages, and were measured by the concordance index (C-index), the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and calibration plots. Results Of 70,605 patients acquired, 21% had HNM and 79% had BM. The HNM group contained more older patients, male sex and lentigo maligna melanoma, and more frequently had thicker tumors and metastases than the BM group. The 5-year cancer-specific survival (CSS) and overall survival (OS) rates were 88.1 ± 0.3% and 74.4 ± 0.4% in the HNM group and 92.5 ± 0.1% and 85.8 ± 0.2% in the BM group, respectively. Eight variables (age, sex, histology, thickness, ulceration, stage, metastases, and surgery) were identified to construct nomograms of CSS and OS for patients with HNM or BM. Additionally, four dynamic nomograms were available on web. The internal and external validation of each nomogram showed high C-index values (0.785–0.896) and AUC values (0.81–0.925), and the calibration plots showed great consistency. Conclusions The characteristics of HNM and BM are heterogeneous. We constructed and validated four nomograms for predicting the 3-, 5- and 10-year CSS and OS probabilities of patients with HNM or BM. These nomograms can serve as practical clinical tools for survival prediction and individual health management.

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