International metastatic renal cell carcinoma database consortium classification and regression tree analysis to characterize objective response rates to first line in metastatic renal cell carcinoma - Summary - MDSpire

International metastatic renal cell carcinoma database consortium classification and regression tree analysis to characterize objective response rates to first line in metastatic renal cell carcinoma

  • By

  • Martin Zarba

  • Dylan O’Sullivan

  • David Maj

  • Winson Y. Cheung

  • Lisa Ludwig

  • Connor Wells

  • Evan Ferrier

  • Razane El Hajj Chehade

  • Frede Donskov

  • Marc Eid

  • Sumanta Kumar Pal

  • Benoit Beuselinck

  • Rana R. McKay

  • Lori Wood

  • Jae Lyun Lee

  • Cristina Suárez

  • Kosuke Takemura

  • Ignacio Duran

  • Toni K. Choueiri

  • Daniel YC Heng

  • May 4, 2026

  • 0 min

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Objective:

To identify subgroups of patients with metastatic renal cell carcinoma (mRCC) who have a high probability of response to first-line systemic treatment using machine learning techniques.

Key Findings:
  • 2,549 patients included, with an overall response rate (ORR) of 36.0%.
  • VEGF inhibitors had the lowest ORR at 29.6%, while IO-IO and IO-TKI combinations had ORRs of 39.1% and 50.2%, respectively.
  • Five key variables identified: therapy type, nephrectomy, lung metastasis, other sites of metastasis, and age.
  • The highest ORR was in patients treated with IO-TKI and nephrectomy (54.9%) and IO-IO with nephrectomy and lung metastasis (59.8%).
  • Factors associated with poorer ORR included non-clear cell histology, older age, bone and liver metastases, poor performance status, elevated neutrophils, and poor IMDC risk score.
  • Patient demographics included 73.2% male and 13.5% with non-clear cell histology.
Interpretation:

The study suggests that treatment selection for mRCC could be optimized by considering identified hierarchical variables, particularly therapy type, which may enhance clinical decision-making.

Limitations:
  • The study is retrospective and may be subject to selection bias, potentially affecting the generalizability of the findings.
  • Further validation of the findings is needed in independent cohorts.
Conclusion:

This large-scale ML analysis highlights the potential for improved treatment selection in mRCC based on specific clinical variables.

Original Source(s)

International metastatic renal cell carcinoma database consortium classification and regression tree analysis to characterize objective response rates to first line in metastatic renal cell carcinoma

  • by Martin Zarba, Dylan O’Sullivan, David Maj, Winson Y. Cheung, Lisa Ludwig, Connor Wells, Evan Ferrier, Razane El Hajj Chehade, Frede Donskov, Marc Eid, Sumanta Kumar Pal, Benoit Beuselinck, Rana R. McKay, Lori Wood, Jae Lyun Lee, Cristina Suárez, Kosuke Takemura, Ignacio Duran, Toni K. Choueiri, Daniel YC Heng

  • May 4, 2026

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