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Development and validation of a nomogram to predict survival in patients with metastatic testicular germ cell tumors.
Yu, Dong-Dong; Hui, Dong; Chen, Wei-Kang; Xiao, Yun-Bei; Wu, Zhi-Gang; Wang, Qin-Quan; Zhou, Chao-Feng; Chen, Zhi-Xia; Li, Cheng-Di; Cai, Jian.
Afiliación
  • Yu DD; Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
  • Hui D; Department of Respiratory Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
  • Chen WK; Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
  • Xiao YB; Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
  • Wu ZG; Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
  • Wang QQ; Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
  • Zhou CF; Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
  • Chen ZX; Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
  • Li CD; Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
  • Cai J; Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
Transl Cancer Res ; 9(4): 2402-2415, 2020 Apr.
Article en En | MEDLINE | ID: mdl-35117600
ABSTRACT

BACKGROUND:

To develop a nomogram to predict cancer-specific survival (CSS) in patients with metastatic testicular germ cell tumors (mTGCTs).

METHODS:

Data were obtained from the Surveillance, Epidemiology, and End Results database. Univariate and multivariate Cox regression models were used to identify factors associated with CSS. Survival times between different groups were compared using Kaplan-Meier survival curves and the log-rank test. A nomogram visualization model was established using the R language to predict survival rates. Harrell's concordance index (C-index), the area under the receiver operating characteristic curve (AUC) and calibration plots were used to assess the performance of the model.

RESULTS:

We analyzed the data of 949 patients. The median follow-up time was 32 months (range 0 to 83 months), and 224 (23.60%) patients died before the last follow-up, of whom 193 (20.33%) died of mTGCTs. The site of distant metastases was an independent prognostic factor for CSS. Compared to patients without involvement of the corresponding organ, patients with bone, brain, liver, and lung involvement had worse CSS. We also found that age, histological type, surgery, radiation therapy, chemotherapy, metastatic site and insurance status affected the CSS of patients with mTGCTs. We used these prognostic factors to construct our nomogram. Harrell's C-index for CSS was 0.739. The AUC and calibration plots indicated good performance of the nomogram.

CONCLUSIONS:

A nomogram for predicting CSS in patients with mTGCTs has been developed, which can help patients and clinicians accurately predict mortality risk and recommend personalized treatment modalities.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Transl Cancer Res Año: 2020 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Transl Cancer Res Año: 2020 Tipo del documento: Article País de afiliación: China