Kidney Cancer Journal 41
Optimizing Prognostication in mRCC:
Recent Advances and New Directions,
From the Bench to the Bedside
Abstract
Histopathologic, clinical and laboratory factors have long
been the hallmarks of prognostic classification schemes
in metastatic renal cell carcinoma (mRCC). This review
offers an outline of state-of-the-art thinking with regard
to these traditional variables and provides insights on current
and future directions to envision how prognostic
models will evolve in the burgeoning field of immuneoncology
therapies. Molecular and genomic biomarkers
are essentially leading the way, potentially reshaping trial
design, and ultimately, risk stratification in clinical
practice.
Introduction
Over the last decade, targeted and immune checkpoint
blockade-based treatments have ushered in a new era in
the management of metastatic renal cell carcinoma
(mRCC). The mRCC treatment approach is currently in
a state of flux, reflecting the rapid pace with which innovative
therapies and strategies, including targeted therapies
(TTx) and immune checkpoint inhibitors (ICP) used
in combination or sequential approaches, are being studied.
These novel treatment options are setting new
benchmarks for progression-free survival (PFS) and overall
survival (OS).1,2,3
Precision medicine is based on the use of individual
prognostic and predictive factors to inform treatment decisions.
On the one hand, prognostic tools help the clinician
to predict the course of the disease and the clinical
outcome with the standard therapy. On the other hand,
predictive factors are associated with the likelihood of response
to a specific therapy and allow the identification
of patients who may, or may not, benefit from a particular
treatment.4 With regards to clinical and experimental
oncologic practices, the identification of prognostic
factors is critical to support patient counseling, guide therapy
selection, design rational clinical trials and interpret
clinical trial results.
The prognostic models currently used in clinical
practice are mainly the Memorial Sloan Kettering Cancer
Center (MSKCC) and the International Metastatic RCC Database
Consortium (IMDC) models.5,6 They took root from
the cytokines and TTx periods, respectively. Both rely on
a number of histopathologic, clinical and biochemical parameters.
New DNA sequencing and proteomic technologies
have fueled the identification of an exciting range
of molecular and genomic factors that could potentially
be used to determine prognosis and to predict response
to treatment.
As cutting-edge therapies and strategies are rapidly
being integrated in the mRCC treatment algorithm, it is
time to take a fresh look at prognostication. New prognostic
factors are emerging, and while the traditional system
such as the IMDC prognostic model is still con-
sidered optimal in clinical practice, it is pending reevaluation
with new standards of care. This review chronicles
the evolution of state-of-the-art prognostication in
mRCC. Our review also highlights some gaps and limitations
associated with the use of traditional models and
addresses crucial questions underlying the research being
done.
Prognostic Models in First-Line Therapy
A number of prognostic models have been proposed, and
they all share various histopathologic, clinical and biochemical
criteria. These models included the Cleveland
Clinic Foundation (CCF) model7, the French model8, the
International Kidney Cancer Working Group (IKCWG)
model9, the Memorial Sloan-Kettering Cancer Center
(MSKCC) model5, and the International Metastatic RCC
Database Consortium (IMDC) prognostic model.6 (Table
1).
In the first-line setting, the two most widely used prognostic
models are the MSKCC and IMDC models. Both
are practical and used dichotomized variables to stratify
risk in three groups: favorable, intermediate and poor.
The MSKCC model was derived from patients treated in
Marie-France Savard, MD, FRCPC
Tom Baker Cancer Centre,
Department of Oncology,
Cumming School of Medicine,
University of Calgary
Calgary, Alberta, Canada
Keywords: metastatic renal cell carcinoma, prognostication, prognostic
model, prognostic factor, predictive factor, molecular biomarker, genomic
biomarker, International Metastatic RCC Database Consortium
(IMDC), Memorial Sloan Kettering Cancer Center (MSKCC), precision
medicine
Corresponding Author: Daniel Y.C. Heng MD, MPH, FRCPC, Tom Baker
Cancer Centre,1331 - 29th St NW, Calgary, Alberta T2N 4N2
Tel: (403) 521-3166 Fax: (403) 283-1651
E-mail: daniel.heng@albertahealthservices.ca
Daniel Y.C. Heng, MD, MPH, FRCPC
Tom Baker Cancer Centre,
Department of Oncology,
Cumming School of Medicine,
University of Calgary
Calgary, Alberta, Canada
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