A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients With Clear Cell Renal Cell Carcinoma: A Population-Based Study

Zhanghuang, Chenghao; Wang, Jinkui; Zhang, Zhaoxia; Jin, Liming; Tan, Xiaojie; Mi, Tao; Liu, Jiayan; Li, Mujie; He, Dalin

doi:10.3389/fpubh.2021.833970

Cited by 8 publications

(6 citation statements)

References 48 publications

(47 reference statements)

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“…Previous virus studies have developed nomograms for predicting the OS and CSS of multiple databases. Moreover, it has shown promising clinical potential value in renal cancer, endometrial stromal sarcoma, glioma, nephroblastoma, and other cancers (18)(19)(20).…”

Section: Discussionmentioning

confidence: 99%

A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients Undergoing Surgery With Prostate Cancer: A Population-Based Study

Zhang

Zhanghuang

Wang

et al. 2022

Front. Public Health

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ObjectiveProstate cancer (PC) is the second leading cause of cancer death in men in the United States after lung cancer in global incidence. Elderly male patients over 65 years old account for more than 60% of PC patients, and the impact of surgical treatment on the prognosis of PC patients is controversial. Moreover, there are currently no predictive models that can predict the prognosis of elderly PC patients undergoing surgical treatment. Therefore, we aimed to construct a new nomogram to predict cancer-specific survival (CSS) in elderly PC patients undergoing surgical treatment.MethodsData for surgically treated PC patients aged 65 years and older were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to identify independent risk factors for elderly PC patients undergoing surgical treatment. A nomogram of elderly PC patients undergoing surgical treatment was developed based on the multivariate Cox regression model. The consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve were used to test the accuracy and discrimination of the predictive model. Decision curve analysis (DCA) was used to examine the potential clinical value of this model.ResultsA total of 44,975 elderly PC patients undergoing surgery in 2010–2018 were randomly assigned to the training set (N = 31705) and validation set (N = 13270). the training set was used for nomogram development and the validation set was used for internal validation. Univariate and multivariate Cox regression model analysis showed that age, marriage, TNM stage, surgical style, chemotherapy, radiotherapy, Gleason score(GS), and prostate-specific antigen(PSA) were independent risk factors for CSS in elderly PC patients undergoing surgical treatment. The C index of the training set and validation indices are 0.911(95%CI: 0.899–0.923) and 0.913(95%CI: 0.893–0.933), respectively, indicating that the nomogram has a good discrimination ability. The AUC and the calibration curves also show good accuracy and discriminability.ConclusionsTo our knowledge, our nomogram is the first predictive model for elderly PC patients undergoing surgical treatment, filling the gap in current predictive models for this PC patient population. Our data comes from the SEER database, which is trustworthy and reliable. Moreover, our model has been internally validated in the validation set using the C-index,AUC and the and the calibration curve, showed that the model have good accuracy and reliability, which can help clinicians and patients make better clinical decision-making. Moreover, the DCA results show that our nomogram has a better potential clinical application value than the TNM staging system.

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Section: Discussionmentioning

confidence: 99%

A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients Undergoing Surgery With Prostate Cancer: A Population-Based Study

Zhang

Zhanghuang

Wang

et al. 2022

Front. Public Health

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“…It is well known that the chance of genetic mutations causing cancer increases with age. Studies have shown that age plays a key role in the survival of various cancers ( 15 , 16 ). A prediction study on non-spermatogonial cell tumors found that the survival rate of adolescent patients was higher than that of adults ( 17 ).…”

Section: Discussionmentioning

confidence: 99%

Develop and validate nomogram to predict cancer-specific survival for patients with testicular yolk sac tumors

Wang²,

Li³

et al. 2022

Front. Public Health

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PurposeTesticular yolk sac tumor (TYST) is a rare malignant germ cell tumor that mainly occurs in young men. Due to the low incidence of yolk sac tumors, there is a lack of prospective cohort studies with large samples. We aimed to develop a nomogram to predict cancer-specific survival (CSS) in patients with TYST.Materials and methodsPatient information was downloaded from the Surveillance, Epidemiology and End Results (SEER) database. We enrolled all patients with TYST from 2000 to 2018, and all patients were randomly divided into a training set and a validation set. Univariate and multivariate Cox proportional hazards regression models were used to identify independent risk factors for patients. We constructed a nomogram based on the multivariate Cox regression model to predict 1-, 3-, and 5-year CSS in patients with TYST. We used a series of validation methods to test the accuracy and reliability of the model, including the concordance index (C-index), calibration curve and the area under the receiver operating characteristic curve (AUC).Results619 patients with TYST were enrolled in the study. Univariate and multivariate Cox regression analysis showed that age, T stage, M stage and chemotherapy were independent risk factors for CSS. A nomogram was constructed to predict the patient's CSS. The C-index of the training set and the validation set were 0.901 (95%CI: 0.859–0.847) and 0.855 (95%CI: 0.865–0.845), respectively, indicating that the model had excellent discrimination. The AUC showed the same results. The calibration curve also indicated that the model had good accuracy.ConclusionsIn this study, we constructed the nomogram for the first time to predict the CSS of patients with TYST, which has good accuracy and reliability and can help doctors and patients make clinical decisions.

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“…A nomogram is a popular prognostic tool with the ability to predict clinical events by integrating potential risk factors (3). Nomograms have been widely used for tumor prognosis (4)(5)(6) and have been effectively used to predict short-term and long-term survival for asymptomatic adults undergoing screening for cardiac risk factors (7). Thus, we hypothesized that a nomogram may also be feasible for the risk stratification of critically ill patients undergoing ECMO.…”

Section: Open Access Edited Bymentioning

confidence: 99%

Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients

Cui

Zha²,

Zhang³

et al. 2023

Front. Med.

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ObjectiveTo investigate the factors of 30-day survival in ECMO patients, establish a nomogram model, and evaluate the predictive value of the model.MethodsA total of 105 patients with extracorporeal membrane oxygenation (ECMO) were admitted to the Department of Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, from January 2018 to March 2021. Cox regression analysis screened out the risk factors. Based on the results of multivariate analysis, the nomogram model was established by using R software, and the discrimination of the model was verified by bootstrap and calibration.ResultsThe results showed that sex, acute physiology and chronic health evaluation (APACHE) II score, disseminated intravascular coagulation (DIC) score before ECMO initiation and average daily dose of norepinephrine were independent risk factors for prognosis. Verify that the nomogram model is verified by bootstrap internally, and the corrected C-index is C-index: 0.886, showing a good degree of discrimination. The calibration curve (calibration) showed that the nomogram model had good agreement. The decision curve analysis(DCA) curve shows good clinical validity above the two extreme curves. Kaplan–Meier curves were drawn for patients in the tertile and compared with the first and second groups. The third group predicted the worst 30-day prognosis for ECMO patients.ConclusionThe nomogram prediction model constructed based on the sex, APACHE II and DIC score, average daily dose of norepinephrine can effectively screen out the factors affecting the prognosis and provide a reference for individualized treatment of ECMO patients.

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A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients With Clear Cell Renal Cell Carcinoma: A Population-Based Study

Cited by 8 publications

References 48 publications

A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients Undergoing Surgery With Prostate Cancer: A Population-Based Study

A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients Undergoing Surgery With Prostate Cancer: A Population-Based Study

Develop and validate nomogram to predict cancer-specific survival for patients with testicular yolk sac tumors

Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients

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