Toward a new staging system for prostate cancer, and why it matters


Date:
October 22, 2020
Source:
Michigan Medicine - University of Michigan
Summary:
The development and validation of a staging system for
non-metastatic prostate cancer could help doctors and patients
assess treatment options, as well as improve clinical trials.



FULL STORY ========================================================================== Doctors and biostatisticians at the University of Michigan Rogel Cancer
Center have led the development and validation of a staging system to
better predict outcomes and inform treatment decisions for men diagnosed
with non-metastatic prostate cancer.


========================================================================== Although it is one of the most common cancers worldwide, prostate
cancer remains one of the few major cancers for which the familiar,
numerical staging system -- ranging from stage 1 to stage 4 -- has not
been adopted into national guidelines for treatment or for the testing
of new medicines in clinical trials.

The new proposed system -- dubbed STAR-CAP -- which appears in JAMA
Oncology, draws on patient, tumor and outcomes data from nearly 20,000
patients from 55 centers in the U.S., Canada and Europe to create a
robust model with strong prognostic power.

"Localized prostate cancer is sometimes less aggressive, sometimes more
-- and whether we're patients, physicians or researchers, we all want to
know as best we can how aggressive a particular cancer is likely to be,"
says study co-first author Robert Dess, M.D., an assistant professor of radiation oncology at Michigan Medicine. "That information helps with
our conversations with patients, it helps with clinical trial design
and it is particularly valuable when you can make those estimates
based off of standard information that you would collect when you
first see a patient to discuss their treatment options." The system
assigns patients to a particular stage through a point system based on
several key variables. These include the patient's age, tumor category,
Gleason grade of cell abnormality and prostate-specific antigen levels,
also known as PSA levels. And STAR-CAP uses more granularity in these categories than many of the previous models, the authors note.

The model divides patients into nine stages of non-metastatic prostate
cancer based on their point score -- from stage 1 to stage 3, with each
stage split into substages of A, B and C.



========================================================================== STAR-CAP's predictions outperformed or equaled previous, non-validated
models, including the current American Joint Committee on Cancer staging system, the study notes. And for a significant number of patients, the
new model would reclassify them as having less advanced disease -- 22%
of patients, for example, who would be classified as stage 3A under the
AJCC's 8th edition criteria would be classified as stage 1C using the
STAR-CAP system, a downgrade of four classification steps.

"This is the kind of information that can give patients and doctors more confidence when discussing treatment options and expected outcomes,"
Dess says.

Several years ago, the AJCC established criteria to evaluate prediction
models for the staging of prostate cancer -- however, since no models
met the criteria, the most recent staging designations were based on the consensus of experts in the field, says study co-senior author Daniel
Spratt, M.D., the Laurie Snow Endowed Research Professor of Radiation
Oncology at Michigan Medicine.

"None of the previous models evaluated met the criteria, so none
of them could be used," Spratt says. "So we said, 'Well, let's make
one.' We wanted it to be transparent, robust and validated, so that we
can start moving closer to communicate using a common staging system,
similar to other cancers. Right now we primarily categorize people as
low risk, intermediate risk or high risk - - which is a fairly blunt
and imprecise system." Moreover, the new scoring system is designed to
be able to be used worldwide with information that is commonly gathered
about a patient and their cancer.



========================================================================== "We're leveraging a backbone of more than three decades of research,"
Dess says. "And we wanted to do it in a formal way and provide the best validated prognostic system we could come up with that was simple, easy
to use, and that relied on readily available information." The team has
made the scoring system available to doctors and researcher worldwide
via a web-based app at STAR-CAP.org.

"We know that some of the newest tools that we have that are just coming
online like genomics or molecular imaging may improve upon this system,
but we wanted to create the best, most widely accessible model based on
the data we currently have -- understanding that new tools may help us
develop even better models in the future," Dess says.

Both Dess and Spratt stressed that the effort would not have been possible without co-first author Krithika Suresh, Ph.D., a former biostatistics
graduate student, and co-senior author Matthew Schipper, Ph.D., a research professor of biostatistics at the School of Public Health and research associate professor of radiation oncology at Michigan Medicine, who led
the work's complex statistical analyses. Elizabeth Chase, a doctoral
candidate in biostatistics was also instrumental, helping to design and
develop the online web application, they said.

Nor would the work have been possible without the participation of
numerous national and international collaborators.

"This work doesn't get done unless you have the collaborative spirit of investigators across the country and around world," Dess adds.


========================================================================== Story Source: Materials provided by
Michigan_Medicine_-_University_of_Michigan. Original written by Ian
Demsky. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Robert T. Dess, Krithika Suresh, Michael J. Zelefsky, Stephen J.

Freedland, Brandon A. Mahal, Matthew R. Cooperberg, Brian
J. Davis, Eric M. Horwitz, Martha K. Terris, Christopher L. Amling,
William J. Aronson, Christopher J. Kane, William C. Jackson, Jason
W. D. Hearn, Curtiland Deville, Theodore L. DeWeese, Stephen Greco,
Todd R. McNutt, Daniel Y.

Song, Yilun Sun, Rohit Mehra, Samuel D. Kaffenberger, Todd
M. Morgan, Paul L. Nguyen, Felix Y. Feng, Vidit Sharma, Phuoc
T. Tran, Bradley J.

Stish, Thomas M. Pisansky, Nicholas G. Zaorsky, Fabio Ynoe
Moraes, Alejandro Berlin, Antonio Finelli, Nicola Fossati,
Giorgio Gandaglia, Alberto Briganti, Peter R. Carroll,
R. Jeffrey Karnes, Michael W. Kattan, Matthew J. Schipper,
Daniel E. Spratt. Development and Validation of a Clinical
Prognostic Stage Group System for Nonmetastatic Prostate Cancer
Using Disease-Specific Mortality Results From the International
Staging Collaboration for Cancer of the Prostate. JAMA Oncology,
2020; DOI: 10.1001/jamaoncol.2020.4922 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/10/201022123111.htm

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