Optimal hour of immune checkpoint inhibitors (ICIs) administration in metastatic renal cell carcinoma (mRCC): The “Tic-Tac” study.

G Giulia Mammone (Department of General Medical Oncology, UZ Leuven, Leuven, Belgium) O Octavie Demeulenaere (Cell Stress & Immunity, Department of Cellular & Molecular Medicine, KU Leuven, Leuven, Belgium) E Edward Scott McTaggart (Computational Oncology Lab, Leuven, Belgium) S Stefan Naulaerts (Computational Oncology Lab, Leuven, Belgium) M Maarten Albersen (Department of Urology, University Hospital Leuven, Leuven, Belgium) M Marcella Baldewijns (Department of Pathology, University Hospital Leuven, Leuven, Belgium) L Liesbeth De Wever (Department of Radiology, University Hospital Leuven, Leuven, Belgium) P Paul M. Clement (Department of Oncology, KU Leuven, Leuven, Belgium) P Paulien Van Loocke (KU Leuven, Leuven, Belgium) L Lisa Kinget (Department of General Medical Oncology, UZ Leuven, Leuven, Belgium) P Philip R. Debruyne (Kortrijk Cancer Centre, Department of Medical Oncology, General Hospital Groeninge, Kortrijk, Belgium) A Annouschka Laenen (Interuniversity Centre for Biostatistics and Statistical Bioinformatics, Leuven Cancer Institute, Leuven, Belgium) A Abhishek Garg (Laboratory of Cell Stress & Immunity (CSI), Department of Cellular and Molecular Medicine, Leuven, Belgium) B Benoit Beuselinck (University Hospital Leuven, KU Leuven, Leuven, Belgium)

Abstract

452 Background: Recent studies suggest that early time-of-day (ToD) ICI-administration improves outcomes in metastatic cancer pts, likely due to circadian regulation of the immune response. Data in mRCC are limited, with no consensus on ToD cut-off or optimal number of morning-administered ICI cycles. Methods: This retrospective study included clear cell mRCC pts treated with ICIs (2015-2025). ToD was recorded for the first 4 treatment cycles. Pearson’s correlation tested ToD variation across the first 4 cycles. ToD was analyzed as a continuous predictor of cancer-specific survival (CSS) using Cox models. Kaplan-Meier analysis compared CSS between ToD cut-off groups. Results: Median follow-up of 223 pts was 28 months (mo): 100 received first-line ipilimumab–nivolumab and 123 later-line nivolumab. Median age at the start of ICIs was 67 years (range 54-69), 71% were men, and 25% had IMDC poor risk. The mean ToD for the first 4 ICI cycles was 13:09, 13:37, 13:39 and 13:31 respectively, with significant correlations between cycle 1 and subsequent cycles. Univariable analysis showed a linear negative association between ToD and CSS across the first 4 cycles, but on multivariable analysis (MVA) only ToD of cycle 1 was independently correlated to CSS (Table). Hence, focus was placed on cycle 1. Pts (n=36) receiving cycle 1 <11:00 had a CSS of 71 months versus 34 mo in pts (n=187) who received cycle 1 >11:00 [HR 0.53 (95%CI 0.3-0.8), p=0.01]. Pts (n=115) receiving cycle 1 <13:00 had a CSS of 62 mo versus 28 mo in pts (n=108) who received cycle 1 >13:00 [HR 0.55 (0.4-0.8), p=0.0006]. Pts (n=190) receiving cycle 1 <16:00 had a CSS of 49 mo versus 19 mo in pts (n=33) who received cycle 1 >16:00 [HR 0.40 (0.2-0.7), p<0.0001). The HR for CSS yielded 0.27 (0.1-0.5, p<0.0001) when comparing pts treated <11:00 with pts treated >16:00. On MVA including ToD at cycle 1, age, IMDC risk, ICI type, and the presence of liver, brain, or bone metastases, ToD at cycle 1 remained independently associated with CSS, with a linear negative effect [HR (+1 hour) 1.1 (1.03-1.2); p = 0.008]. Poor IMDC risk [HR 1.9 (1.1-3.6), p=0.04], older age [HR (+1 year) 1.03 (1.01-1.04); p=0.005], and liver metastases [HR 1.7 (1.1-2.5); p=0.03] were independently linked to worse CSS. Conclusions: Consistent with previous findings showing improved outcomes in mRCC patients who received ICIs in the morning, our study confirms that earlier ICI-administration (especially <11:00) is associated with better CSS. ToD of the first treatment cycle carries the greatest impact on CSS in mRCC. Univariable and multivariable analysis: ToD administration cycle 1-4. ToD Univariable analysisN=223 Multivariable analysisN=180 HR (+ 1 hour) (CI); p-value Cycle 1 1.2 (1.1-1.3); 0.0001 1.1 (1.05-1.3); 0.005 Cycle 2 1.1 (1.04-1.2); 0.003 1.0 (0.9-1.1); 0.9 Cycle 3 1.1 (1.03-1.2); 0.008 1.0 (0.9-1.2); 0.6 Cycle 4 1.1 (1.04-1.2); 0.007 1.1 (0.9-1.2); 0.2

Article Details

Volume / Issue Vol. 44, Issue 7_suppl
Published March 01, 2026
Pages 452-452
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (14)

G

Giulia Mammone

Department of General Medical Oncology, UZ Leuven, Leuven, Belgium

O

Octavie Demeulenaere

Cell Stress & Immunity, Department of Cellular & Molecular Medicine, KU Leuven, Leuven, Belgium

E

Edward Scott McTaggart

Computational Oncology Lab, Leuven, Belgium

S

Stefan Naulaerts

Computational Oncology Lab, Leuven, Belgium

M

Maarten Albersen

Department of Urology, University Hospital Leuven, Leuven, Belgium

M

Marcella Baldewijns

Department of Pathology, University Hospital Leuven, Leuven, Belgium

L

Liesbeth De Wever

Department of Radiology, University Hospital Leuven, Leuven, Belgium

P

Paul M. Clement

Department of Oncology, KU Leuven, Leuven, Belgium

P

Paulien Van Loocke

KU Leuven, Leuven, Belgium

L

Lisa Kinget

Department of General Medical Oncology, UZ Leuven, Leuven, Belgium

P

Philip R. Debruyne

Kortrijk Cancer Centre, Department of Medical Oncology, General Hospital Groeninge, Kortrijk, Belgium

A

Annouschka Laenen

Interuniversity Centre for Biostatistics and Statistical Bioinformatics, Leuven Cancer Institute, Leuven, Belgium

A

Abhishek Garg

Laboratory of Cell Stress & Immunity (CSI), Department of Cellular and Molecular Medicine, Leuven, Belgium

B

Benoit Beuselinck

University Hospital Leuven, KU Leuven, Leuven, Belgium