Frontiers in Oncology (Jan 2022)

Selection of Optimal Candidates for Cytoreductive Nephrectomy in Patients with Metastatic Clear Cell Renal Cell Carcinoma: A Predictive Model Based on SEER Database

  • Yishan Zhang,
  • Yishan Zhang,
  • Yishan Zhang,
  • Jintao Hu,
  • Jintao Hu,
  • Jintao Hu,
  • Jingtian Yang,
  • Jingtian Yang,
  • Jingtian Yang,
  • Yingwei Xie,
  • Yingwei Xie,
  • Yingwei Xie,
  • Zhiliang Chen,
  • Zhiliang Chen,
  • Zhiliang Chen,
  • Wentai Shangguan,
  • Wentai Shangguan,
  • Wentai Shangguan,
  • Jinli Han,
  • Jinli Han,
  • Jinli Han,
  • Wang He,
  • Wang He,
  • Wang He,
  • Jingyin Yang,
  • Jingyin Yang,
  • Jingyin Yang,
  • Zaosong Zheng,
  • Zaosong Zheng,
  • Zaosong Zheng,
  • Qiyu Zhong,
  • Qiyu Zhong,
  • Qiyu Zhong,
  • Dingjun Zhu,
  • Dingjun Zhu,
  • Dingjun Zhu,
  • Wenlian Xie,
  • Wenlian Xie,
  • Wenlian Xie

DOI
https://doi.org/10.3389/fonc.2022.814512
Journal volume & issue
Vol. 12

Abstract

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BackgroundCurrently, the progress of targeted drugs in the treatment of metastatic clear cell renal cell carcinoma (mccRCC) is limited. Cytoreductive nephrectomy (CN), as an alternative treatment, can improve the prognosis of patients with metastatic renal cell carcinoma to some extent. However, it is unclear which patients would benefit from this tumor reduction operation. As a consequence, we developed a predictive model to identify patients who may well benefit from CN in terms of survival.MethodsWe identified patients with metastatic clear cell renal cell carcinoma retrospectively from the Surveillance, Epidemiology, and End Results (SEER) database (2010–2015) and classified them into surgery and non-surgery groups. Propensity score matching (PSM) was performed to balance the baseline characteristics. Patients who survived longer than the median overall survival (OS) of no-surgery group were defined as surgical-benefit patients. Then, we developed a predictive model based on preoperative characteristics using multivariable Logistic regression. Calibration curves and the area under the receiver operating characteristic (AUC) were used to evaluate the efficiency of the predictive model. The clinical value of the nomogram was assessed utilizing decision curve analysis (DCA).ResultsOur study collected 5544 patients from the SEER database, with 2352(42.4%) receiving cytoreductive surgery. Overall survival (OS) was longer in the CN group than in the non-surgery group after 1:1 propensity scoring matching (median OS: 19 months vs 7 months; hazard ratio (HR) =0.4106, P< 0.001). In the matched surgery group, 65.7% (367) patients survived more than 7 months after the operation and they were considered to benefit from CN. The predictive model performed well on both the training group (AUC=73.4%) and the validation group (AUC=71.9%) and the calibration curves indicated a high degree of consistency. The decision curve analysis curve demonstrated the clinical utility. We classified surgical patients into the beneficial group and non-beneficial group by using the predictive model, then discovered a substantial difference in OS between the two groups.ConclusionsWe developed a nomogram to select ideal mccRCC patients who might benefit from cytoreductive nephrectomy. Clinicians could make a more precise treatment strategy for mccRCC patients.

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