Abstract
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.
Highlights
Bladder cancer (BLCA) accounts for the most common urinary malignancy with high mortality rate [1]
The prespecified variables were as follows: age, race, sex, marital status, year of diagnosis, Tumor grade, Histology, TNM stages based on the American Joint Commission on Cancer (AJCC) 7th edition, radiation, chemotherapy, vital status, and survival month
The results showed that age, race, sex, marital status, histology, TNM stages based on the AJCC 7th edition, radiation, and chemotherapy were prognostic factors for overall survival in patients with BLCA (Table 2)
Summary
Bladder cancer (BLCA) accounts for the most common urinary malignancy with high mortality rate [1]. Surgery is indicated for non-metastatic BLCA, with transurethral resection of bladder tumor (TURBT) for the non-muscle-invasive and radical cystectomy (RC) for the muscle-invasive. For non-muscle-invasive BLCA with intermediate to high risk, intravesical chemotherapy is one of the first-line treatments [5, 6]. Neoadjuvant cisplatin-based chemotherapy followed by RC or chemoradiation combined with maximal TURBT are recommended [7]; the overall 5-year survival rate of these patients remains less than 50% [8,9,10]. Metastatic muscle-invasive disease can be treated with systemic chemotherapy and immunotherapy, which yields 5-year survival rates of 5% with distant metastasis and 36% with regional metastasis [7]. The overall survival of BLCA remains relatively low despite multiple treatment modalities. It is important to develop prognostic model for overall survival of BLCA patients, as identifying patients with poor estimated survival outcomes may guide enhanced therapies for these subjects in an effort to improve prognosis [11]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
