| BackgroundUrinary bladder carcinoma is one of the most common malignancy with?77,000 new cases and 16,000 deaths per year in the USA.It has several histological types including transitional cell carcinoma(TCC),squamous cell carcinoma(SCC),adenocarcinoma,small cell carcinoma and other less common types.Among them,the majority is transitional cell carcinoma accounting for?90-95%of urinary bladder carcinoma while squamous cell carcinoma only accounts for 2-5%.Therefore,people have more research attention on transitional cell carcinoma rather than squamous cell carcinoma because of the incidence.But squamous cell carcinoma of the bladder still has a high degree of malignity and high incidence of recurrence.Moreover,for patients with stage? or IV bladder cancer,squamous cell carcinoma had a more rapid disease course than transitional cell carcinoma.So,it is very necessary to understand squamous cell carcinoma better especially for prognosis in order to guide clinicians make individual treatment for those patients with different survival outcomes.Owing to the low incidence of squamous cell carcinoma of the bladder,there have been still lack of a visible and accurate model to predict its prognosis still now.Nomograms are commonly used tools to estimate prognosis in oncology and medicine.With the ability to generate an individual numerical probability of a clinical event by integrating diverse prognostic and determinant variables,nomograms fulfill our desire for biologically and clinically integrated models and our drive towards personalized medicine.In short,medical nomograms use biologic and clinical variables,such as tumor grade and patient age,to graphically depict a statistical prognostic model that generates a probability of a clinical event,such as cancer recurrence or death,for a given individual.Rapid computation through user friendly digital interfaces,together with increased accuracy,and more easily understood prognoses compared to conventional staging,allow for seamless incorporation of nomogram derived prognosis to aid in clinical decision making.Therefore,there are increasing presence of nomograms in the Internet and medical journals,and the use of nomograms by patients and physicians is increasing.ObjectiveOn the basis of some significant clinical parameters,we had an intent to establish nomograms for estimating patients' prognosis with squamous cell carcinoma(SCC)of the urinary bladder including overall survival(OS)and cancer specific survival(CS S)MethodsWe collected data from 1210 patients with bladder squamous cell carcinoma diagnosed between 2004 and 2014 in the Surveillance,Epidemiology,and End Results(SEER)database,which covers approximately 30%of the US population and correlates tumors.The important clinical pathological parameters,demographic information,and treatment methods were organized and analyze and analyzed,and the Cox proportional hazard regression model was used for statistical analysis to establish a nomogram.The consistency of the nomogram is verified by an internal queue using the consistency index(C-index)to test the accuracy of the nomogram.ResultsSeveral common indicators were taken into these two nomograms(OS and CSS)including age,marriage,sex,TNM staging system,radical cystectomy,tumor size and lymph node ratio while the OS nomogram contained race,grade and chemotherapy additionally.They had an excellent predictive accuracy on 1-and 3-year OS and CSS with C-indices of 0.748 for OS and 0.741 for CSS.Besides,all calibration curves also showed a great consistency between actual survival and predictive survival.ConclusionTo a large extent,the nomograms quietly improved the accuracy and applicability on predicting survival outcome of patients with squamous cell carcinoma of the urinary bladder,which would provide a reliable and reasonable tool to help clinicians evaluate high-risk patients and make individual treatment strategies. |
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