Cytoreductive nephrectomy in metastatic renal cell carcinoma: outcome of patients treated with a multidisciplinary, algorithm-driven approach
2020
Metastatic renal cell carcinoma (mRCC) represents a significant and rising burden of disease, with rapidly evolving treatment modalities. The role of cytoreductive nephrectomy (CN) is controversial in this setting. As such, London Cancer has pursued a multidisciplinary team (MDT) approach when assessing suitability for surgery. A retrospective analysis of treatment-naive synchronous mRCC patients, managed via a renal-specialist MDT, was conducted between January 2015 and December 2018. An MDT selection algorithm for CN—using the International Metastatic Renal Cell Carcinoma Database Consortium score (IMDC), performance status and metastatic disease burden—was developed. 87 treatment-naive synchronous mRCC patients received either CN (n = 18), Systemic therapy (ST) alone (n = 43) or Best supportive care (BSC) (n = 26). Progression free survival (PFS) and overall survival (OS) were assessed. 51% and 39% were IMDC intermediate and poor risk. Median PFS was 28.6 months and 4.5 months in the CN group and ST alone group, respectively, Hazard Ratio for death was 3.63 [(95% CI 1.68–7.83) p < 0.05]. OS remains immature for the CN group, but a median OS of 12.8 months was observed in the ST group and 5.0 months for BSC. 1-year OS rate for CN, ST and BSC groups was 77.8%, 55.8% and 23.10%, respectively. These findings describe outcomes of an unselected series of patients treated via an MDT-driven, protocolised treatment pathway. MDT pathway-based decision making may improve patient selection for CN. Further research is needed to evaluate the role of CN amongst a growing landscape of treatment strategies, including immune checkpoint inhibitors and combination therapies. Multi-disciplinary team, pathway-based treatment strategy may improve patient selection for cytoreductive nephrectomy in patients with metastatic renal cell carcinoma.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
17
References
3
Citations
NaN
KQI