Shuxiong Zeng1, Lihe Dai1, Jun Yang1, Xiaomin Gao1, Xiaowen Yu2, Qian Ren1, Kaijian Wang1, Jinshan Xu1, Zeyu Yang1, Bo Yang1, Huiqing Wang1, Qing Yang1, Huamao Ye1, Jianguo Hou1, Yue Pan3, Zhensheng Zhang1, Zhiliang Weng3, Yinghao Sun4, Chuanliang Xu5. 1. Department of Urology, Changhai Hospital, Second Military Medical University, Shanghai, PR China. 2. Department of Geriatrics, Changhai Hospital, Second Military Medical University, Shanghai, PR China. 3. Department of Urology, The First Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou, PR China. 4. Department of Urology, Changhai Hospital, Second Military Medical University, Shanghai, PR China. Electronic address: sunyh@medmail.com.cn. 5. Department of Urology, Changhai Hospital, Second Military Medical University, Shanghai, PR China. Electronic address: xuchuanliang@vip.126.com.
Abstract
OBJECTIVE: To create multivariable models with readily available clinicopathologic variables for predicting the prognosis of upper tract urothelial carcinomas (UTUC). PATIENTS AND METHODS: We retrospectively analyzed patients diagnosed as UTUC and underwent radical nephroureterectomy in 2 high volumes, tertiary care centers. A total of 445 patients and 227 patients met the inclusion criteria were included for constructing the prediction model and external validation, respectively. Univariable and multivariable Cox regression models were used to analyze independent risk factors, and nomogram and calibration curve were constructed by R project. RESULTS: The median follow-up for the development and external validation cohorts were 33.5 and 32.5 months, respectively. Multivariable analysis detected older age (≥65 years), with concurrent bladder cancer at diagnosis, with both ureter and renal pelvic tumor, lymphovascular invasion, urothelial carcinoma with divergent differentiation, higher pathological grade and stage, and positive lymph node were significantly associated with poorer outcome of UTUC. The c-index of the nomogram with these above-mentioned independent risk factors to predict the cancer specific survival was 0.74 (95% CI, 0.64-0.84) and 0.73 (95%CI, 0.59-0.87) for the development cohort and external validation cohort, respectively. CONCLUSIONS: We developed and externally validated a novel and accurate nomogram with readily available clinicopathological information for predicting the cancer specific survival of UTUC. This nomogram could help clinicians stratify patients with UTUC into different risk groups with distinct prognosis by the total scores obtained from the prediction tool, thus facilitate decision-making and clinical trial designing.
OBJECTIVE: To create multivariable models with readily available clinicopathologic variables for predicting the prognosis of upper tract urothelial carcinomas (UTUC). PATIENTS AND METHODS: We retrospectively analyzed patients diagnosed as UTUC and underwent radical nephroureterectomy in 2 high volumes, tertiary care centers. A total of 445 patients and 227 patients met the inclusion criteria were included for constructing the prediction model and external validation, respectively. Univariable and multivariable Cox regression models were used to analyze independent risk factors, and nomogram and calibration curve were constructed by R project. RESULTS: The median follow-up for the development and external validation cohorts were 33.5 and 32.5 months, respectively. Multivariable analysis detected older age (≥65 years), with concurrent bladder cancer at diagnosis, with both ureter and renal pelvic tumor, lymphovascular invasion, urothelial carcinoma with divergent differentiation, higher pathological grade and stage, and positive lymph node were significantly associated with poorer outcome of UTUC. The c-index of the nomogram with these above-mentioned independent risk factors to predict the cancer specific survival was 0.74 (95% CI, 0.64-0.84) and 0.73 (95%CI, 0.59-0.87) for the development cohort and external validation cohort, respectively. CONCLUSIONS: We developed and externally validated a novel and accurate nomogram with readily available clinicopathological information for predicting the cancer specific survival of UTUC. This nomogram could help clinicians stratify patients with UTUC into different risk groups with distinct prognosis by the total scores obtained from the prediction tool, thus facilitate decision-making and clinical trial designing.
Authors: Maximilian Pallauf; Frederik König; David D'Andrea; Ekaterina Laukhtina; Hadi Mostafaei; Reza Sari Motlagh; Fahad Quhal; Abdulmajeed Aydh; Takafumi Yanagisawa; Tatsushi Kawada; Pawel Rajwa; Lukas Lusuardi; Francesco Soria; Pierre I Karakiewicz; Morgan Rouprêt; Michael Rink; Yair Lotan; Vitaly Margulis; Nirmish Singla; Evanguelos Xylinas; Shahrokh F Shariat; Benjamin Pradere Journal: Front Oncol Date: 2022-07-01 Impact factor: 5.738