Survival Analysis and a Novel Nomogram Model for Progression-Free Survival in Patients with Prostate Cancer

Han, Yuefu; Wen, Xingqiao; Chen, Dong; Li, Xiaojuan; Leng, Qu; Wen, Yuehui; Li, Jun; Zhu, Weian

doi:10.1155/2022/6358707

Cited by 2 publications

(2 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nomograms, a statistic-based tool, can assess the risk of clinicopathological features by quantifying the biological and clinical variables of patients with cancer (6). To date, nomograms have been widely applied in the personalized prediction of cancer, such lung, cervical, prostate, and hepatocellular carcinomas (7)(8)(9)(10)(11). To the best of our knowledge, several studies have reported risk factors associated with breast cancer (12)(13)(14)(15)(16)(17).…”

Section: Introductionmentioning

confidence: 99%

A nomogram for survival prediction in 275,812 U.S. patients with breast cancer: a population-based cohort study based on the SEER database

Wang¹,

Xing²,

X³

et al. 2022

Gland Surg

View full text Add to dashboard Cite

Background: Nomograms can assess the risk of clinicopathological features by quantifying the biological and clinical variables of cancer patients. However, the nomogram based on significant factors that influence the survival of breast cancer in a large population has been rarely explored. This study was to investigate the predictive effectiveness of a nomogram for the survival of patients with breast cancer. Methods: Demographic and clinical data of 275,812 breast cancer patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. All patients aged ≥20 years in this retrospective cohort study were classified as two groups in a random manner, namely the training set (n=193,069) and validation set (n=82,743). The outcomes of our study were the 3-and 5-year survival of breast cancer. The potential predictors of cancer mortality were screened by univariate and multivariable Cox regression analyses. The nomogram was conducted based on the predictors. Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curve was utilized to evaluate the performance of the nomogram.Results: The age at diagnosis, race, marital status, tumor size, first malignant primary indicator, American Joint Committee on Cancer (AJCC) T stage, M stage, tumor grade, and number of malignant tumors were independent predictors for the death of patients with breast cancer. The C-indexes of the training set and the validation set were 0.782 and 0.778, respectively. The area under the curve (AUC) values of the nomogram for predicting the 3-and 5-year survival of breast cancer were 0.770 and 0.756, respectively. Furthermore, the C-index values of our nomogram were 0.816, 0.775, 0.773, 0.734, and 0.750 for predicting survival in Asian, White, Hispanic, American Indian, and Black populations, respectively. Conclusions:The nomogram may have predictive performance for predicting the 3-and 5-year survival of breast cancer patients, and future studies need to validate our findings.

show abstract

Section: Introductionmentioning

confidence: 99%

A nomogram for survival prediction in 275,812 U.S. patients with breast cancer: a population-based cohort study based on the SEER database

Wang¹,

Xing²,

X³

et al. 2022

Gland Surg

View full text Add to dashboard Cite

show abstract

“…Hu et al developed a prognostic prediction model based on 22 autophagy-related genes expressed in PC patients ( 11 ). Han et al conducted a prognostic nomogram for progression-free survival of 255 PC patients ( 12 ). However, the clinical applicability of these models is limited by the need to collect clinical samples and predictive ability.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a nomogram for predicting the overall survival of prostate cancer patients: a large population-based cohort study

Zhou¹,

Pu²,

Wei³

et al. 2022

Transl Androl Urol

View full text Add to dashboard Cite

Background: Prostate cancer (PC) is the second most common malignant tumor, and its survival is of great concern. However, the assessment of survival risk in current studies is limited. This study is to develop and validate a nomogram for the prediction of survival in PC patients using data from the Surveillance, Epidemiology, and End Results (SEER) database. Methods: A total of 153,796 PC patients were included in this cohort study. Patients were divided into a training set (n=107,657) and a testing set (n=46,139). The 3-, 5-and 10-year survival of the PC patients were regarded as the outcomes. Predictors based on the demographic and pathological data for survival were identified by multivariate Cox regression analysis to develop the predictive nomogram. Internal and subgroup validations were performed to assess the predictive performance of the nomogram. The C-index, time-dependent receiver operating characteristic (ROC) curves, and corresponding areas under the ROC curves (AUCs) were used to estimate the predictive performance of the nomogram. Results: Age at diagnosis, race, marital status, tumor node metastasis (TNM) stage, prostate specific antigen (PSA) status, Gleason score, and pathological stage were identified as significantly associated with the survival of PC patients (P<0.05). The C-index of the nomogram indicated a moderate predictive ability [training set: C-index =0.782, 95% confidence interval (CI): 0.779-0.785; testing set: C-index =0.782, 95%CI: 0.777-0.787]. The AUCs of this nomogram for the 3-, 5-, and 10-year survival were 0.757 (95% CI: 0.756-0.758), 0.741 (95% CI: 0.740-0.742), and 0.716 (95% CI: 0.715-0.717), respectively. The results of subgroup validation showed that all the AUCs for the nomogram at 3, 5, and 10 years were more than 0.70, regardless of marital status and race. Conclusions:We developed a nomogram with the moderate predictive ability for the long-term survival (3-, 5-, and 10-year survival) of patients with PC.

show abstract

Survival Analysis and a Novel Nomogram Model for Progression-Free Survival in Patients with Prostate Cancer

Cited by 2 publications

References 25 publications

A nomogram for survival prediction in 275,812 U.S. patients with breast cancer: a population-based cohort study based on the SEER database

A nomogram for survival prediction in 275,812 U.S. patients with breast cancer: a population-based cohort study based on the SEER database

Development and validation of a nomogram for predicting the overall survival of prostate cancer patients: a large population-based cohort study

Contact Info

Product

Resources

About