The prognostic nomogram including MRI for locally advanced prostate cancer treated by radical prostatectomy

Wang, Yan; Wu, Guangyu; Fan, Liancheng; Pan, Jiahua; Gong, Yuping; Fei, Xiaochen; Du, Xin; Zhu, Yao; Xue, Wei

doi:10.1002/pros.24126

Cited by 4 publications

(3 citation statements)

References 33 publications

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“…Further research should investigate novel imaging application tools for the prediction of BLCA survival outcomes, as the role of multiparametric MRI (mpMRI) within nomograms has been demonstrated in prostate cancer (41,42). Besides, the newly released Vesical Imaging-Reporting and Data System (VI-RADS) based on mpMRI data has shown promises for accurate preoperative BLCA staging (43)(44)(45), which could be exploited for the estimation of cancer-specific and overall survival.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Prognostic Model for Predicting Overall Survival in Patients With Bladder Cancer: A SEER-Based Study

Wang

Liu

2021

Front. Oncol.

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ObjectiveTo establish a prognostic model for Bladder cancer (BLCA) based on demographic information, the American Joint Commission on Cancer (AJCC) 7th staging system, and additional treatment using the surveillance, epidemiology, and end results (SEER) database.MethodsCases with BLCA diagnosed from 2010–2015 were collected from the SEER database, while patient records with incomplete information on pre-specified variables were excluded. All eligible cases were included in the full analysis set, which was then split into training set and test set with a 1:1 ratio. Univariate and multivariate Cox regression analyses were conducted to identify prognostic factors for overall survival (OS) in BLCA patients. With selected independent prognosticators, a nomogram was mapped to predict OS for BLCA. The nomogram was evaluated using receiver operating characteristic (ROC) analysis and calibration plot in both the training and test sets. The area under curve [AUC] of the nomogram was calculated and compared with clinicopathological indicators using the full analysis set. Statistical analyses were conducted using the R software, where P-value <0.05 was considered significant.ResultsThe results indicated that age, race, sex, marital status, histology, tumor-node-metastasis (TNM) stages based on the AJCC 7th edition, and additional chemotherapy were independent prognostic factors for OS in patients with BLCA. Patients receiving chemotherapy tend to have better survival outcomes than those without. The proposed nomogram showed decent classification (AUCs >0.8) and prediction accuracy in both the training and test sets. Additionally, the AUC of the nomogram was observed to be better than that of conventional clinical indicators.ConclusionsThe proposed nomogram incorporated independent prognostic factors including age, race, sex, marital status, histology, tumor-node-metastasis (TNM) stages, and additional chemotherapy. Patients with BLCA benefit from chemotherapy on overall survival. The nomogram-based prognostic model could predict overall survival for patients with BLCA with accurate stratification, which is superior to clinicopathological factors.

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Section: Discussionmentioning

confidence: 99%

Development and Validation of a Prognostic Model for Predicting Overall Survival in Patients With Bladder Cancer: A SEER-Based Study

Wang

Liu

2021

Front. Oncol.

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“…Our nomogram was established using clinical features that are easily collected in the clinical setting. Another model proposed by Wang et al , combines the method of treatment, hyperintensity within the prostate on diffusion-weighted imaging (DWI), and the metastasis burden of pelvic lymph nodes to assess the survival of PC patients ( 29 ). However, the predictive performance of this system was not evaluated and the small sample size (n=121) may weaken the reliability of this model.…”

Section: Discussionmentioning

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

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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.

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“…While genetics, hormones, and other factors play a major role in the development of prostate cancer, a comprehensive risk stratification framework appears to be incomplete without gland anatomic characteristics. Commonly used calculations such as PSA density based on total prostate volume could be supplanted with a more detailed model with PSA, urine test, PI‐RADS, and MRI‐based zonal metrics 33,34 …”

Section: Discussionmentioning

confidence: 99%

Benign prostate hyperplasia as a potential protective factor against prostate cancer: Insights from a magnetic resonance imaging study of compositional characteristics

et al. 2021

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Purpose The structural relationship between benign prostate hyperplasia (BPH) and prostate cancer (Pca) is controversial. The purpose of our study was to examine the association between quantitative prostate compositional metrics by magnetic resonance imaging (MRI) and Pca. Methods We identified 405 patients who underwent prostate MRI and biopsy and/or prostatectomy from January 2019 to January 2021 at our institution. Segmentation volumetric methods were used to assess central gland (CG) and peripheral zone (PZ) volume. PZ mean thickness and mean apparent diffusion coefficient (ADC), marker of underlying histologic components, were measured. Multivariable logistic regression was performed with outcomes of ≥Grade Group (GG) 2 Pca and for multifocal disease. Results On multivariable analysis, higher CG volumes were at lower odds of ≥GG2 disease (n = 227) (OR: 0.97, 95% CI 0.96–0.98, p < 0.0001), taking into account PZ volume (p = 0.18) and thickness (p = 0.70). For every one cc increase in CG volume, there was an approximately 3% decrease in odds of ≥GG2 disease. Similar findings were noted for multifocal disease (n = 180) (OR: 0.97, 95% CI 0.96–0.98, p < 0.0001). Notably, ADC of the normal PZ was not significantly associated with CG volume (p = 0.21) nor a predictor of disease (p = 0.49). Conclusions Increasing central gland volume, driven by BPH, is associated with lower odds of significant Pca, including multifocal disease, while PZ anatomic and histologic surrogate changes were noncontributory. Findings support BPH impediment of global tumor growth predicted by theoretical mechanobiological model. This potential stabilizing factor should be further studied for risk stratification and in consideration for BPH therapy.

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The prognostic nomogram including MRI for locally advanced prostate cancer treated by radical prostatectomy

Cited by 4 publications

References 33 publications

Development and Validation of a Prognostic Model for Predicting Overall Survival in Patients With Bladder Cancer: A SEER-Based Study

Development and Validation of a Prognostic Model for Predicting Overall Survival in Patients With Bladder Cancer: A SEER-Based Study

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

Benign prostate hyperplasia as a potential protective factor against prostate cancer: Insights from a magnetic resonance imaging study of compositional characteristics

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